Applies to General Signal Processing

2 x Professor / Reader of Machine Learning and Artificial Intelligence

Department of Computer Science
University of Surrey
Guildford, UK

https://jobs.surrey.ac.uk/037121 

The Department of Computer Science at the University of Surrey seeks to recruit two research leaders with an international profile and an outstanding research and publication track record to lead a substantial and sustained portfolio of research in any of the following areas within Machine Learning (ML) and Artificial Intelligence (AI):

• Trustworthy AI (explainable, secure and privacy preserving machine learning)
• Deep learning for natural language processing
• Computational neuroscience and machine learning
• Distributed machine learning and optimization
• AI planning and optimal control

The Department of Computer Science has a world-class reputation in these areas and regularly publishes at top-level conferences and journals. The Department is home to the Nature Inspired Computing and Engineering (NICE) group. The group has 10 academics and holds world-leading expertise in evolutionary computation, computational neuroscience, autonomous and self-organising systems, reinforcement learning, Bayesian learning, privacy-preserving machine learning, explainable AI, computer vision, and image and natural language processing. The research group maintains close links with leading industries, the public sector, and governmental bodies, leading to a strong heritage of real-world impact.

The NICE group is a key partner in the new Surrey Institute for People-Centred AI, a major strategic investment bringing together world-leading expertise in fundamental AI theory with cross-university domain expertise to realise and shape AI impact for public good. It is expected that the postholders will play a leading role in this new Institute.

Each successful candidate will have proven success in leading multi-Faculty research proposals and securing funding through collaborative group bids. One postholder will also be considered for the strategic leadership role of the Head of the NICE group. Each postholder will also take an active role in training the ML scientists of the future by leading teaching activities at both undergraduate and postgraduate level within the University’s School of Computer Science and Electronic Engineering.

These are full-time and permanent positions. The postholders will benefit from a dynamic working environment on a leafy campus close to London, with access to world-class leisure facilities nearby. The role brings a substantial salary and generous relocation package, as well as a variety of academic and professional development opportunities.

The qualifications required and job specification is detailed in the job profile. In addition to completing the online application form, please submit:

• A two-page supporting statement on your future research and research leadership plans
• Your CV
• A list of your publications and externally funded research projects (if not included in your CV)

Interviews will be held remotely in September. Positions are available for immediate appointment and the candidates will be expected to start as early as possible after that and no later than March / April 2022.

Our staff and students come from all over the world and the Department is proud of its friendly and inclusive culture. The University and the Department specifically are committed to building a culturally diverse organisation. Applications are strongly encouraged from female and minority candidates. The Department of Computer Science was awarded a Bronze Athena SWAN award, in recognition of our commitment to equality and diversity.

Applicants are encouraged to check the associated role profile for this post. Informal enquiries are welcomed by Dr Mark Manulis (m.manulis@surrey.ac.uk). Otherwise, we look forward to receiving your online application at: https://jobs.surrey.ac.uk/037121 

Postdoctoral fellowship in Image processing for flood detection (in Sao Paulo, Brazil)

The Computational Imaging Lab in the Department of Computer Science at Portland State University is hiring a graduate student starting Winter/Spring 2022. This is a fully funded PhD student position and includes a monthly stipend and tuition waiver. The position will be for 1 year, initially, and will be renewed for up to a maximum of 5 years (subject to satisfactory progress and availability of funding).

We are developing next generation cameras and algorithms that can capture images in challenging conditions where conventional cameras struggle: imaging in extremely dark or extremely bright environments, imaging high resolution 3D structures from long distances, and imaging through poor visibility like smoke and fog. We envision a future where such cameras will improve everyone’s quality of life: computer vision systems for autonomous cars that make drivers and pedestrians safer, high-precision cameras for surgical robots, and image sensors that improve accuracy of medical diagnoses.

The ideal candidate will have a Bachelor's degree in CS/CE/EE or a related field, strong communication and writing skills, and a keen desire to solve real-world problems. We are looking for candidates who are strong in some of the areas listed below, and are eager to learn more about areas that aren’t currently their strength:
- Mathematical background in calculus, linear algebra and probability
- Programming experience in Matlab/Python/R, C/C++
- Machine learning experience with libraries like PyTorch or TensorFlow
- Some hands-on electronics prototyping experience (e.g. Arduino)

Computational imaging is a highly interdisciplinary research area. The success of our lab will depend on a truly interdisciplinary team with researchers from diverse backgrounds. We especially encourage students who are historically under-represented in computer science and engineering to apply.This includes but is not limited to women, students with disabilities, socio-economically disadvantaged groups, and first-generation college students.

Portland State University is a public university known nationally for its innovation, community engagement and sustainability initiatives. Its urban setting and its unique relationship to city and regional agencies provides a living laboratory for urban research and industry and government collaboration. The Portland area is home to numerous technology companies including Google, Intel, Apple, Amazon and Nvidia that collectively employ more than 40,000 people.

More details here.

PhD Studentship - UCL Institute of Healthcare Engineering EPSRC PhD Studentships on Healthy Ageing

Project Title:  Lab-on-an-App: AI Empowered Point-of-Care Diagnostics for Ageing Population

Project Supervisor:

• Professor Miguel Rodrigues | Dept Electronic and Electrical Engineering | University College London

Project Co-Supervisors:

• Dr Mine Orlu / UCL School of Pharmacy | University College London
• Professor Andreas Demosthenous / Dept Electronic and Electrical Engineering | University College London

Project Collaborators:

• Dr Moe  Elbadawi / UCL School of Pharmacy | University College London
• Professor Abdul Basit  / UCL School of Pharmacy | University College London
• Dr Adam Daneshmend / Imperial College Healthcare NHS Trust

Deadline: The closing date is 30th June 2021.

Project Description

Mobile health technology – encompassing mobile sensor, computation, communication, and user-interface capability – has the potential to support healthcare of an increasingly ageing population. It offers the opportunity to perform clinical diagnoses on the patient side, contributing to a more sustainable demand for healthcare systems in developed nations but also more widespread use of healthcare in developing ones. The overarching challenge relates to the development of high-accuracy, low-cost, portable mobile health applications capable of diagnosing a range of conditions prevalent in the older population.

One such condition relates to anaemia that nowadays afflicts circa 20% of the older population. This condition is both under-recognised and under-treated; leads to additional morbidities ranging from organ damage (heart, lung), immune system disorders, or fatigue in turn contributing to falls (hence bone fractures); and contributes to the financial burden of healthcare systems. Adults with some types of anaemias were considered as a vulnerable patient group requiring shielding due to their high risk of severe SARS-CoV-2 infection during the COVID-19 pandemic.

The diagnosis of anaemia requires laboratory-based measurements of a venous blood sample but this is not always readily accessible to a large fraction of the older population, preventing timely interventions. Therefore, with an increasing number of diagnoses reported each year, there is also a demand for easily accessible portable diagnosic tools.

This project will develop a Lab-on-App to non-invasively diagnose anaemia and its causes (e.g. genetics, diet, or injury) that can be easily used by older people, carers, or healthcare professionals. It involves the development of:

(1) Sensor technology capable of extracting information / images from the body or body fluids including (i) electrochemical sensors to measure concentration of urea on urine or (ii) multi-spectral sensors to measure skin / body fluids appearance

(2)  Machine learning technology that delivers diagnoses of anaemia and its causes given the data collected by the aforementioned sensors.

(3) An android / ios application offering users an interface to collect data, analyse data, and deliver the diagnostics. 

This project also involves collaboration with multiple departments within UCL, along with our NHS partner. Interactions are also planned with other stakeholders notably the UCL Institute of Healthcare Engineering (IHE) (https://www.ucl.ac.uk/healthcare-engineering/ ).

It is anticipated that the successful demonstration of our proposed Lab-on-App will lead to additional work by this team using mobile health technology to diagnose other conditions afflicting older population (kidney diseases, colon diseases, or vitamin deficiencies).

Funding :

This is a fully funded 4-year studentship covering fees (home rate) and maintenance stipend at the UCL EPSRC DTP enhanced rate (£18,609 in 2021/22, rises with inflation each year). It also covers an RTSG (Research Training Support Grant) of up to £4,800 to cover additional costs of training eg courses, project costs, conferences, travel.

Studentships are automatically renewed each year provided that sufficient academic progress is made. 

Qualifications required: 

Candidates should have or expect to achieve an excellent degree(s) (BEng/MEng/MSc) in Electronic/Electrical Engineering, Computer Science or related disciplines. The ideal candidate would have experience/knowledge on one of the followings: 

• Hardware / Sensor Technology
• Machine Learning Technology
• Healthcare technology
• Python or related programming languages

The ideal candidate should also be passionate about healthcare, along with how technology can make a difference in healthcare. The ideal candidate will also have excellent communication skills in order to interact with researchers from various disciplines.

Eligibility:

Applicants must fulfil the academic entry requirements for the programme they are applying to. In addition, applicants must also fulfil eligibility criteria based on nationality / residency specified below:

Funding eligibility criteria based on nationality

• UK nationals are eligible provided they meet residency requirements.
• EU nationals with settled status are eligible.
• EU nationals with pre-settled status are eligible provided they meet residency requirements.
• Irish nationals living in UK or Ireland are eligible.
• Those who have indefinite leave to remain or enter are eligible.
• All others are classified as "International".

Residency requirements for UK nationals

• Living in EEA or Switzerland on 31-Dec-2020 (at that time UK was considered part of EEA) and lived in UK, EEA, Switzerland, or Gibraltar for at least 3 years immediately before the studentship begins.
• Lived continuously in UK, EEA, Switzerland, or Gibraltar between 31-Dec-2020 and the start of the studentship.

Residency requirements for EU, EEA, or Swiss nationals with pre-settled status

• Living in UK by 31-Dec-2020 (a requirement to receive pre-settled status).
• Living in UK, EEA, Switzerland, or Gibraltar for at least 3 years immediately before the studentship begins.

These studentships are offered with open eligibility, however the number of International students which can be recruited is capped according to the EPSRC terms and conditions.

How to apply:

Applications must be made using the UCL online application system (https://www.ucl.ac.uk/prospective-students/graduate/apply) and Applications should be made using the UCL postgraduate study application form. Please mark it to the attention of ICE/Rodrigues.

The application must be accompanied by a personal statement that includes how the candidate experience aligns with the proposed research; a curriculum vitae (with publications if any); and two references.

The successful applicant is expected to start on 27-Sep-2021.

Contact:

For informal enquires please contact Prof. Miguel Rodrigues (m.rodrigues@ucl.ac.uk), Prof Andreas Demosthenous (a.demosthenous@ucl.ac.uk), or Dr. Mine Orlu (m.orlu@ucl.ac.uk)

About UCL, the Department of Electronic and Electrical Engineering and the School of Pharmacy

University College London (UCL) was founded in 1826 as the third university in England, after Oxford and Cambridge. UCL is the first university in England to admit students of any race, class or religion, and the first to welcome women on equal terms with men. UCL is organized into 11 constituent faculties, within which there are over 100 departments, institutes and research centres. UCL has 983 professors and more than 7000 academic staffs who are dedicated to research and teaching of the highest standards. Its student community is almost 36,000, the largest in the UK. There are 29 Nobel Prize winners and three Fields medalists amongst UCL’s alumni and current and former staff. UCL is the top rated university in the UK for research excellence (REF2014). It has a strong tradition and large knowledge base in medical research with a dedicated institute on Healthcare Engineering and 10+ hospitals. UCL has world-class support for researchers and has been voted the best place for postdoctoral researchers to work for consecutive years by The Scientist magazine. The main campus of UCL is located in central London, close to British Museum, West-End and Thames River. 

The Department of Electronic and Electrical Engineering at UCL was established by Professor Sir Ambrose Fleming in 1885 and has a very strong research culture, state-of-the-art research equipment and facilities, and a very rich history of many fundamental research achievements in electronic and electrical engineering. The department has received top ratings in every UK research evaluation carried out to date. 

The UCL School of Pharmacy is one of the Divisions located within the Faculty of Life Sciences (FLS). The Faculty has been associated with seven Nobel Laureates and continues to build on its existing strengths in cell and developmental biology, evolutionary and population genetics, cellular and circuits neuroscience, and structural and molecular biology. 

The Division is one of the UK’s leading centres of pharmacy education and research it enjoys a lively and stimulating academic environment in which teachers, researchers, professionals and students interact. All are connected by an interest in medicines - how they work, how they are made and how they are used by people to prevent and treat disease. Research focuses on advancing and understanding medicines and health care, and in creating new medicines. Our performance in the Research Excellence Framework 2014 marks UCL School of Pharmacy as one of the most important centres for pharmacy research in UK education. 

Further information regarding UCL may be found at: www.ucl.ac.uk/

Information about the departments may be found at: www.ucl.ac.uk/eee and http://www.ucl.ac.uk/pharmacy/

Research Fellow in Machine Learning for Sound Location: University of Surrey, Guildford, UK Closing Date: Wednesday 16 June 2021 (23:00 GMT) Applications are invited for a 3-year Research Fellow in Machine Learning for Sound, to work full-time on an EPSRC-funded Fellowship project "AI for Sound" (https://ai4s.surrey.ac.uk/), to start on 1 July 2021 or as soon as possible thereafter. We would particularly like to encourage applications from women, disabled and Black, Asian & Minority Ethnic candidates, since these groups are currently underrepresented in our area.

The aim of the project is to undertake research in computational analysis of everyday sounds, in the context of a set of real-world use cases in assisted living in the home, smart buildings, smart cities, and the creative sector. The postholder will be responsible for the core machine learning parts of the project, investigating advanced machine learning methods applied to sound signals. The postholder will be based in the Centre for Vision, Speech and Signal Processing (CVSSP) and work under the direction of PI (EPSRC Fellow) Prof Mark Plumbley. The successful applicant is expected to have a PhD (gained or near completion) in electronic engineering, computer science or a related subject; and research experience in machine learning and audio signal processing. Research experience in one or more of the following is desirable: deep learning; model compression; differential privacy; active learning; audio feature extraction; and publication of research software and/or datasets.

CVSSP is an International Centre of Excellence for research in Audio-Visual Machine Perception, with 170 researchers, a grant portfolio of £30M (£21M EPSRC) from EPSRC, EU, InnovateUK, charity and industry, and a turnover of £7M/annum. The Centre has state-of-the-art acoustic capture and analysis facilities and a Visual Media Lab with video and audio capture facilities supporting research in real-time video and audio processing and visualisation. CVSSP has a compute facility with over 200 GPUs for deep learning and >1PB of high-speed secure storage.

For more information about the posts and how to apply, please visit: https://jobs.surrey.ac.uk/026021 Deadline: Wednesday 16 June 2021 (23:00 GMT)

For informal inquiries about the position, please contact Prof Mark Plumbley (m.plumbley@surrey.ac.uk).

What Your Job Will Be Like

We are seeking a driven and results oriented Electrical Engineer to support existing research efforts to test geophysical instrumentation and perform signal analysis of seismic data. All research is team oriented and directed at increasing national and international monitoring capabilities for underground nuclear explosions. Opportunities exist to conduct research on improving methods for signal analysis of unique seismic datasets and interpret the results and communicate findings through presentations and publications.

The projects offer the ability to perform hands-on work designing experimental setups conducting those experiments both in the laboratory and in an outdoor internationally recognized facility. These experiments support real-world deployments of monitoring equipment and offer a chance to combine electrical engineering, mechanical engineering, geophysics, and metrology principles. Additionally, opportunities exist to develop new signal analysis processing techniques to identify hard to distinguish events within time-series data.

On any given day, you may be asked to:

• Responsible for designing and conducting experiments to evaluate the performance of commercially available geophysical instruments in both laboratory and operational conditions
• Identify test metrics and standards for testing environmental variables impacting commercial geophysical instrumentation systems and apply principles of metrology to devise experimental setups for testing
• Collaborate with computer scientists to develop signal detection algorithms
• Modify an existing code base to test a new hypothesis and write data analysis codes to interpret and graph results
• Participate in journal article discussion groups and seminar series, along with drafting publications, reports, and presentations

Qualifications We Require

• Master’s degree in electrical engineering, geophysics, or closely related field, with an emphasis on instrumentation or signal analysis
• Ability to obtain and maintain a DOE Q clearance

Qualifications We Desire

• Experience operating and testing geophysical (seismic and infrasound) instrumentation
• Principles of metrology applied to the calibration of geophysical instrumentation
• Experience in geophysical signal processing
• Possess a strong dedication to positive teaming dynamic, strong written and verbal skills, detail oriented with a focus on customer service
• Proven experience with at least one computer programming language (Java, C++, Python, MATLAB)
• Strong organizational skills and ability to meet scheduled work completion dates
• Proficiency with varied communication methods, including oral presentation, preparation of high-impact visual presentations, written reports, and the ability to clearly and concisely communicate scientific and technical information at a level tailored the audience

About Our Team

We perform geophysical monitoring research and development in support of Sandia's mission as a national security laboratory. The team's geophysics expertise addresses challenges surrounding ground-based nuclear detonation detection through next-generation algorithms exploiting multi-phenomenological data, advanced sensor technologies, and demonstration experiments. We have a wide range of expertise in field seismology, subsurface characterization, seismo-acoustic and infrasound modeling; evaluation of seismic and infrasound sensors and systems; and the processing, analysis, and interpretation of all types of geophysical data. Technical work spans the spectrum from theoretical to applied and includes strong modeling, lab and field data collection, and analysis capabilities. The department serves as Sandia's resource for ground-based monitoring expertise, partnering with departments across the labs to integrate multiple types of data-including optical, seismic, electromagnetic, infrasound, atmospheric, radionuclide-to address broad national security needs.

About Sandia

Sandia National Laboratories is the nation’s premier science and engineering lab for national security and technology innovation, with teams of specialists focused on cutting-edge work in a broad array of areas. Some of the main reasons we love our jobs:
• Challenging work with amazing impact that contributes to security, peace, and freedom worldwide
• Extraordinary co-workers
• Some of the best tools, equipment, and research facilities in the world
• Career advancement and enrichment opportunities
• Flexible work arrangements for many positions include 9/80 (work 80 hours every two weeks, with every other Friday off) and 4/10 (work 4 ten-hour days each week) compressed workweeks, part-time work, and telecommuting (a mix of onsite work and working from home)
• Generous vacations, strong medical and other benefits, competitive 401k, learning opportunities, relocation assistance and amenities aimed at creating a solid work/life balance*

World-changing technologies. Life-changing careers. Learn more about Sandia at: http://www.sandia.gov
*These benefits vary by job classification.

Security Clearance

Sandia is required by DOE to conduct a pre-employment drug test and background review that includes checks of personal references, credit, law enforcement records, and employment/education verifications. Applicants for employment need to be able to obtain and maintain a DOE Q-level security clearance, which requires U.S. citizenship. If you hold more than one citizenship (i.e., of the U.S. and another country), your ability to obtain a security clearance may be impacted.

Applicants offered employment with Sandia are subject to a federal background investigation to meet the requirements for access to classified information or matter if the duties of the position require a DOE security clearance. Substance abuse or illegal drug use, falsification of information, criminal activity, serious misconduct or other indicators of untrustworthiness can cause a clearance to be denied or terminated by DOE, resulting in the inability to perform the duties assigned and subsequent termination of employment.

EEO

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status and any other protected class under state or federal law.

The Department of Signal Processing and Acoustics at the Aalto University School of Electrical Engineering invites applications for

ASSISTANT PROFESSOR IN SIGNAL PROCESSING (tenure track)

Detailed call and instructions how to apply at: https://www.aalto.fi/en/open-positions/assistant-professor-in-signal-processing

The call is in a broad area of signal processing with special emphasis on:

• Signal processing theory and methods
• Signal processing for communications and networking, joint sensing and communication
• Machine learning for signal processing
• Sensor array and multichannel signal processing, radar signal processing
• Signal processing for data science
• Information forensics and security
• Software, circuits and systems for signal processing 

We are seeking outstanding individuals who have demonstrated excellence in addressing the above challenges. As a tenure-track faculty member, you are expected to complement the expertise of the current faculty by bringing new ideas and perspectives into our community. You are also expected to teach signal processing courses in master’s and bachelor’s programmes with a typical teaching load of two courses per year.

Your experience and ambitions

We are looking for applicants with

• A doctorate in signal processing or related field
• A proven ability to carry out high quality research and publish in top venues of the discipline
• Potential to attract research funding and build up your own research group
• An interest to collaborate with industry
• Ability to build a high-level international collaboration network
• Motivation to teach at undergraduate and/or graduate levels

We offer

• A tenure track position with promotion to tenured position based on merits
• A competitive benefits package including access to health care
• Start-up funding and grant writing support to help you establish your own group
• Excellent collaboration possibilities within the university
• Great future in one of the happiest, cleanest and safest countries in the world, with comprehensive social security system and free education up to university level

Scientific environment

The position is situated in the Department of Signal Processing and Acoustics at the Aalto University School of Electrical Engineering. The department conducts world-class research in four research areas and groups: Signal processing, speech processing, acoustics and audio signal processing, and metrology. The Signal Processing group focuses on statistical and array signal processing, wireless communication, optimisation, machine learning, radar and multisensor systems. The department has 12 professors, 4 of whom are IEEE Fellows. Our department’s professorial faculty has been extremely successful in attracting funding from academic, industrial and defence sources. The department has an extensive and active network of collaborators in world-leading academic institutes and industrial research groups.  There are very strong research groups in the areas of Communication Engineering, Radio Engineering and Circuit Design within the School of Electrical Engineering, providing a critical mass of knowledge for large scale cross-disciplinary research projects.

 How to apply

Please submit your application latest on June 18, 2021 through our recruiting system by using the “Apply now!” link below. Please include the following pdf documents in English:

1. Cover letter
2. Curriculum vitae (with contact information and the Researcher ID number)
3. List of publications with the 7 most significant highlighted
4. Research statement describing past research and plans for future research
5. Teaching portfolio describing teaching experience and plans for teaching
6. References from no more than 2 individuals

The application materials should be addressed to the president of Aalto University. The application materials will not be returned. General instructions for applicants including languages requirements and guidelines for compiling the teaching portfolio and CV are at https://www.aalto.fi/en/tenure-track/interested-in-joining-our-tenure-track

Selected candidates will be invited to the Department of Signal Processing and Acoustics and to Aalto University’s Otaniemi campus in August-September 2021. The short-listed candidates’ applications will be submitted for review by external international experts. Selected candidates will, with their consent, be subject to an aptitude assessment.

Aalto University is a community of bold thinkers where science and art meet technology and business. We are committed to identifying and solving grand societal challenges and building an innovative future. Aalto has six schools with nearly 11 000 students and a staff of more than 4000, of which 400 are professors. Our main campus is located in Espoo, Finland. Diversity is part of who we are, and we actively work to ensure our community’s diversity and inclusiveness in the future as well. We warmly encourage qualified candidates from all backgrounds to join our community.

The School of Electrical Engineering promotes high-quality science, technology and innovations for the good of Finnish society and all of humankind. In our environment, the natural sciences, engineering and information technology intertwine to form smart systems and innovations that save energy and promote well-being.  With our research, we seek to respond to many challenges posed by sustainable development and our research is applied in mobile devices, electrical networks and in satellites. One of the school’s special strengths is linking research with the Finnish and international business sector. We have our school around 2000 students and the number of doctoral degrees is 50 and yearly graduated master students around 250. Our personnel consist of 700 people, with over 70 professors.    

The Department of Signal Processing and Acoustics at the Aalto University School of Electrical Engineering invites applications for

ASSISTANT PROFESSOR IN SIGNAL PROCESSING (tenure track)

Signal processing is the enabling technology for the generation, transformation, and interpretation of information touching our daily lives in a myriad of ways. It comprises the theory, algorithms, and applications related to processing information contained in many different formats broadly designated as signals. Signal processing uses mathematical, statistical, and computational methods, modeling techniques and algorithms for generating, transforming, transmitting, and learning from signals. 
  The subfields within signal processing are numerous. The call is in a broad area of signal processing with special emphasis on:

• Signal processing theory and methods
• Signal processing for communications and networking, joint sensing and communication
• Machine learning for signal processing
• Sensor array and multichannel signal processing, radar signal processing
• Signal processing for data science
• Information forensics and security
• Software, circuits and systems for signal processing 

We are seeking outstanding individuals who have demonstrated excellence in addressing the above challenges. As a tenure-track faculty member, you are expected to complement the expertise of the current faculty by bringing new ideas and perspectives into our community. You are also expected to teach signal processing courses in master’s and bachelor’s programmes with a typical teaching load of two courses per year.

Your experience and ambitions

We are looking for applicants with

• A doctorate in signal processing or related field
• A proven ability to carry out high quality research and publish in top venues of the discipline
• Potential to attract research funding and build up your own research group
• An interest to collaborate with industry
• Ability to build a high-level international collaboration network
• Motivation to teach at undergraduate and/or graduate levels

We offer

• A tenure track position with promotion to tenured position based on merits
• A competitive benefits package including access to health care
• Start-up funding and grant writing support to help you establish your own group
• Excellent collaboration possibilities within the university
• Great future in one of the happiest, cleanest and safest countries in the world, with comprehensive social security system and free education up to university level

Aalto tenure track

This position belongs to our tenure track system and will be filled to the assistant professor level. The salary is based on Aalto University salary system, but you can also provide your own salary requests. Getting tenure and advancement on Aalto tenure track is based on an evaluation of your achievements and merits against the Aalto tenure track criteria. Please see the details about the tenure track path at Aalto at https://www.aalto.fi/en/tenure-track/tenure-track-career-path and evaluation criteria at https://www.aalto.fi/services/tenure-track-evaluation-criteria.

Scientific environment

The position is situated in the Department of Signal Processing and Acoustics at the Aalto University School of Electrical Engineering. The department conducts world-class research in four research areas and groups: Signal processing, speech processing, acoustics and audio signal processing, and metrology. The Signal Processing group focuses on statistical and array signal processing, wireless communication, optimisation, machine learning, radar and multisensor systems. The department has 12 professors, 4 of whom are IEEE Fellows. Our department’s professorial faculty has been extremely successful in attracting funding from academic, industrial and defence sources. The department has an extensive and active network of collaborators in world-leading academic institutes and industrial research groups.  There are very strong research groups in the areas of Communication Engineering, Radio Engineering and Circuit Design within the School of Electrical Engineering, providing a critical mass of knowledge for large scale cross-disciplinary research projects.

 How to apply

Please submit your application latest on June 18, 2021 through our recruiting system Welcome to the Aalto University e-recruitment process! (saima.fi). Please include the following pdf documents in English:

1. Cover letter
2. Curriculum vitae (with contact information and the Researcher ID number)
3. List of publications with the 7 most significant highlighted
4. Research statement describing past research and plans for future research
5. Teaching portfolio describing teaching experience and plans for teaching
6. References from no more than 2 individuals

The application materials should be addressed to the president of Aalto University. The application materials will not be returned. General instructions for applicants including languages requirements and guidelines for compiling the teaching portfolio and CV are at https://www.aalto.fi/en/tenure-track/interested-in-joining-our-tenure-track
  Selected candidates will be invited to the Department of Signal Processing and Acoustics and to Aalto University’s Otaniemi campus in August-September 2021. The short-listed candidates’ applications will be submitted for review by external international experts. Selected candidates will, with their consent, be subject to an aptitude assessment.

More information

If you wish to hear more about the position or us, please contact Professor Risto Wichman (risto.wichman@aalto.fi). In case you have questions related to the recruitment process, please contact HR Coordinator Alina Järvinen (alina.jarvinen@aalto.fi). Aalto University reserves the right for justified reasons to leave the position open, to extend the application period and to consider candidates who did not submit applications within the application period.

 About Aalto University, Helsinki and Finnish society

At Aalto, high-quality research, art, education and entrepreneurship are promoted hand in hand. Disciplinary excellence is combined with multidisciplinary activities, engaging both students and the local innovation ecosystem. Our main campus in Otaniemi is quickly transforming into an open collaboration hub that encourages encounters between students, researchers, industry, start-ups and other partners. Aalto University was founded in 2010 as three leading Finnish universities, Helsinki University of Technology, the Helsinki School of Economics and the University of Art and Design Helsinki, were merged to strengthen Finland’s innovative capability.
The greater Helsinki region is a world-class information technology complex, attracting leading scientists and researchers in various fields of electrical engineering.  As a living and working environment, Finland consistently ranks high in quality of life, and Helsinki, the capital of Finland, is regularly ranked as one of the most liveable cities in the world.
Finns are proud to say that we have one of the best education systems in the world. The Nordic values of equality and co-operation are deeply rooted in our society. We are one of the world’s top countries in happiness, clean air and nature, press freedom and consider the many voices in our society a strength. With high investments in R&D, a strong innovation culture, open data and advanced state of digitalization, we are a nation of innovation and entrepreneurship. Gender equality, flexibility and the low hierarchy are at the core of our Nordic working environment. Having four seasons, clean air and thousands of lakes, we are nature-loving people who take good care of our unique environment. For more information about living in Finland: For international staff | Aalto University

Assistant Professor in Signal Processing | Aalto University  

The Department of Neurosurgery seeks a talented postdoctoral research associate to study the neurophysiology of sleep in human subjects, within the combined translational research efforts of Aviva Abosch, MD, PhD, Professor and Chair, Department of Neurosurgery, University of Nebraska Medical Center (UNMC), and Stephen Gliske, PhD, Assistant Professor, Department of Neurosurgery, and Co-Director of the MEG Program, UNMC. This project is NIH-funded and represents a collaborative effort between UNMC, Stanford University (Clete Kushida, MD), University of Colorado Anschutz Medical Campus (John Thompson, PhD), University of Pennsylvania (Casey Halpern, MD), and York University (Joel Zylberberg, PhD). The focus of this position will be on the acquisition and analysis of multi-night recordings of simultaneous scalp EEG, EMG, and intracranial deep brain stimulator (DBS)-recorded local field potential (LFP) data, working at the interface of translational neuroscience, advanced signal processing, and computational physics.

The UNMC Department of Neurosurgery is comprised of eleven faculty members and has numerous close collaborations with other clinical and basic science departments. Specialized services and expertise are offered in areas of functional and stereotactic neurosurgery, endovascular and cerebrovascular neurosurgery, neuro-oncology, complex spine and deformities, and surgical spine oncology.

As Nebraska’s only public academic health sciences center, UNMC is committed to the education of a 21st century health care workforce, to finding cures and treatments for disease, providing the best care for patients, and serving Nebraska and its communities through award-winning research and clinical care.

Required qualifications for this position include a PhD in a relevant field (neural engineering, neuroscience, applied math, electrical engineering, biomedical engineering, physics, or other related field). Also required are excellent leadership, project management, and communication skills, the ability to run experiments independently, to analyze data and to plan future research direction, combined with excellent team skills. We seek a highly self-motivated, inquisitive scientist, with a track-record of publication in peer-reviewed journals

Successful candidates for the role will have experience in data analysis, be fluent in at least one programming/scripting language (e.g., MATLAB, Python, etc.), and have advanced mathematical skills. The ideal candidate will have prior experience in analysis of EEG, LFP, and/or neurostimulation.

This position is available immediately, and applicants are asked to submit a current copy of their CV, a letter of interest outlining relevant experience, as well as the contact information of three references. Applications are being accepted online at https://unmc.peopleadmin.com/postings/58506. Individuals from diverse backgrounds are encouraged to apply.

Autonomous on-board drone navigation (i.e., without human intervention) in inaccessible environments is a fundamental challenge. The goal in this project is to develop novel machine learning algorithms for autonomous drone navigation in outdoor environments including localization and synchronization for BVLOS (beyond visual line of sight) scenarios and/or GPS-denied environments, by utilizing RF signals from fixed ground stations and/or in collaboration with other drones. This includes robust holistic 3D perception through sensor fusion of on-board sensors, for e.g., lidar, radar, camera, and inertial measurement units (IMUs), algorithms for detect and avoid using advanced machine learning for object detection, object classification, and ego-motion estimation. The proposed resource-constrained algorithms will be energy-efficient and robust for in-drone perception, cognition, and control.

About the project The Postdoctoral (and PhD) positions are a part of the recently funded ECSEL-H2020 project named ADACORSA (Airborne data collection on resilient system architectures), with over 50 partners across Europe. Circuits and Systems (CAS) group in the Faculty of EEMCS at TUD is one of the WP leaders (among 8) in this consortium, and will develop ground-breaking algorithms to realize efficient, robust, and data-fusion based cost-effective perception and control for autonomous drones.

The overarching goal of this project is to provide technologies to render drones as a safe and efficient component of the mobility mix, with reliable capabilities in extended BVLOS operations.

More details on the position: https://cas.tudelft.nl/Openings/vacancy.php?id=78

Apply here: https://www.tudelft.nl/over-tu-delft/werken-bij-tu-delft/vacatures/details?jobId=2641&jobTitle=Postdoc%20Machine%20Learning%20for%20Autonomous%20Drone%20Navigation