Signal Processing Theory and Methods

Online Applications only: http://emea3.mrted.ly/28n6x

The University of Luxembourg is a multilingual, international research university.

The Interdisciplinary Centre for Security, Reliability and Trust (SnT) invites applications from PhD candidates in the general area of signal processing for extremely high frequency sensing and communication applications. SnT carries out interdisciplinary research in secure, reliable and trustworthy ICT systems and services, often in collaboration with industrial, governmental or international partners.

Your Role

Position Description:

Radar sensor based driver assistance systems for automotive applications are currently under investigation to increase comfort and safety of drivers.  Presence of radar functionality on multiple cars leads to a network of radar sensors which can be exploited to enhance the environment sensing. An emergent automotive scenario is collaborative sensing, where the cars sense and communicate about the emergency situations (like obstacles, braking, accident etc.). The dynamics of the scenario, e.g., number and position of the cars, preclude a central processing unit there by motivating the network radar. Recent advances in wireless communication technology can be exploited to realize a network radar. Further, due to spectrum allocation trends and requirements of high bandwidth, an investigation of extremely high frequencies, namely mmWave and beyond bands (with a corresponding wavelength of about 1 mm), has been attracting significant attention in both the automotive radar industry as well as the mobile community. Compared to microwaves, operation in higher bands provides access to larger bandwidth enabling higher range resolution and fine details of the targets as well as higher data rates. Besides, the size of system components such as the antennas required to process the such signals reduces drastically; this enables the possibility of accommodating high number of antenna elements on the device to enhance the spatial resolution. Further, their incorporation on a moving platform, e.g., automobile, results in a synthetic aperture radar (SAR) / inverse synthetic aperture radar (ISAR) whose advantages are well documented. However, to explore and exploit the advantages of such network radar systems, several research challenges need to be solved. The research will focus on devising optimization algorithms to enhance the performance of MIMO radar networks in waveform optimization, target detection, classification and localization while leveraging advances in wireless communications.

The position holder will be required to perform the following tasks:

• Carrying out research in the field of signal processing algorithms for MIMO radar networks in extremely high frequencies co-existing with communications
• Disseminating results through scientific publications

For further information, please contact us at Mohammad.Alaee@uni.lu or Bhavani.Shankar@uni.lu

Your Profile

Qualification: The candidate should possess an MSc degree or equivalent in Electrical/Electronic Engineering, Computer Science or Applied Mathematics. The successful candidates will join a strong and motivated research team lead by Prof. Björn Ottersten and Dr. Bhavani Shankar in order to carry out PhD.

Experience: The ideal candidate should have some knowledge and experience in a number of the following topics:

• Signal processing techniques for distributed sensors
• Developing scientific algorithms in the fields of mmWave (and beyond) radar signal/image processing
• Waveform design and optimization algorithms applied to the radar systems
• Machine/Deep Learning with applications to radar systems including Automatic target classification and recognition algorithms (including CNN and DNN)

and have a  strong background in

• Optimization theory
• Linear algebra and statistics
• Statistical Signal processing

Development skills in MATLAB, is required. Exposure to USRP/SDR implementation and familiarity with LabView, C++, and FPGA programming is considered as an advantage.

Language Skills: Fluent written and verbal communication skills in English are required.

We offer

The University offers a Ph.D. study program with a Fixed Term Contract up to 3 years in total, pending satisfaction of progress milestones (CDD), full-time (40 hrs/week). The University is an equal opportunity employer. The candidate will work in an exciting international environment.

Further Information

Application should be sent online, in English and should include:

• Full CV, including list of publications and names (and contact information including email addresses) of three references
• Transcript of all modules and results from university-level courses taken
• Research statement and topics of particular interest to the candidate (300 words).

All qualified individuals are encouraged to apply. The University of Luxembourg is an equal opportunity employer. The last date for application is September 15, 2019. Applications will processed as they arrive; early application is highly encouraged. Please apply online here:  http://emea3.mrted.ly/28n6x

Online Application Only:http://emea3.mrted.ly/28f97

The University of Luxembourg is a multilingual, international research university.

The Interdisciplinary Centre for Security, Reliability and Trust (SnT) invites applications from PhD holders for conducting research in design and optimization methods for performance enhancement of next generation radar networks

SnT is carrying out interdisciplinary research in secure, reliable and trustworthy ICT systems and services, often in collaboration with industrial, governmental or international partners. The SIGCOM group in SnT is pursuing research on automotive radar applications in partnership with IEE (www.iee.lu), a Luxembourg based global leader in automotive safety sensing systems for occupant detection and classification. Recently, Prof. Bjorn Ottersten Director of SnT and head of SIGCOM, has been awarded the prestigious European Research Council (ERC) Advanced Grant to pursue research on cognitive radar systems with applications to automotive radar. For further information, you may visit www.securityandtrust.lu and http://wwwen.uni.lu/snt/research/sigcom.

Project Description

As novel applications emerge, the requirements on radar systems have grown significantly from being “a blip on the radar”, to providing an image like reconstruction of the surroundings. Currently, multi-static and widely-separated MIMO radars offer multi-view perspective. However, these systems suffer from the need for high rate synchronization, lack of performance guarantees, minimal exploitation of advances in waveform processing and machine learning among others. Thus, it is essential to go beyond the mature co-located MIMO and the current widely-separated MIMO radars towards achieving reliable imaging like performance for extended targets. In fact, many of these networks, such as in the automotive scenario, can involve large number of dynamic nodes. This necessitates devising novel radar-network architectures as well as exploring various optimization methodologies for waveform design, super-resolution parameter estimation and decentralized resource allocation.  

This emerging field opens interesting avenues for pursuing research in radar signal processing, especially on

• Relevant architectures for novel radar networks including information exchange mechanisms for identified use cases
• Associated signal processing elements including development of optimization algorithms for waveform, receiver design including high-resolution parameter estimation as well as their adaptation to dynamic scenarios
• System optimization using model based mechanisms as well as machine learning approaches; deep unfolding applications

The research associates will have further the opportunity to work towards in-lab demonstration of the developed techniques using USRP/SDR implementations.

The SIGCOM research group is in a unique position towards realizing the objectives of the project having exposure to radar signal processing through ongoing research projects, evolution of communication standards through participation and contribution as well as experience with prototype chip sets from the test-bench development activity.

Your Role

The successful candidates will join a strong and motivated research team lead by Prof. Björn Ottersten in order to carry out research in the area of signal processing for next generation radar systems.

The position holder will be required to perform the following tasks:

• Shaping research directions in line with project objectives, pursuing research and delivering project outputs
  • Carrying out cutting edge research activities in architectural definition, waveform design and receiver processing, enabling cognition in next generation radar networks
  • Participating in development and upgradation of the SDR based Radar test bench based on pursued research is considered as a plus
• Disseminating the results through scientific publications in high impact factor journals
• Presenting the results in the internationally well-known conferences and workshops
• Attracting funding in cooperation with partners
• Providing guidance to PhD and MSc students
• Assisting in teaching duties
• Organizing relevant workshops

For further information, please contact Bhavani.Shankar@uni.lu or Bjorn.Ottersten@uni.lu

Your Profile

Qualification: The candidate should possess (or be in the process of completing) a PhD degree or equivalent in Electrical/Electronics Engineering, Computer Science or Applied Mathematics.

Experience: The ideal candidate should have research project-based experience (FP7/H2020, Industry) and publication record in a number of the following topics:

• Optimization methodologies with application to Radar Systems
• Machine/Deep Learning with applications to Radar Systems
• Widely-separated MIMO Radar System, Waveform Design and Receiver processing
• Statistical Signal Processing

Exposure to USRP/SDR implementation and familiarity with FPGA programming is considered as an advantage. Development skills in one of the programming languages, MATLAB, LabVIEW or C++ are required.

Exposure to the latest radar technology and digital communications is desirable.

Language Skills: Fluent written and verbal communication skills in English are required.

We offer

The University offers a two-year employment contract that may be extended up to five years. The University is an equal opportunity employer. You will work in an exciting international environment and will have the opportunity to participate in the development of a newly created university.

Further Information

Application should be submitted online and include:

• Full CV, including list of publications and name (and email address, etc.) of three referees
• Transcript of all modules and results from university-level courses taken
• Research statement and topics of particular interest to the candidate (300 words)

Deadline for applications:  September 15, 2019.  Applications will be processed as they arrive; early application is highly encouraged.

The Chair of Theoretical Information Technology has an immediate opening for a

Doctoral student; Postdoctoral student:
Hardware Demonstrator for Post Shannon Communication (E13 TVL) (f/m/d)

for the joint project "Post Shannon Communication," which is being funded by the Federal Ministry of Education and Research (BMBF). In this joint project, transmission systems that go beyond Shannon's communication approach are to be developed in order to achieve more efficient information transmission for selected applications. The position is initially limited to three years. An extension is possible.

Content of the project and areas of responsibility
▪ Construction of a hardware demonstrator
▪ Implementation of the developed transmission methods, to demonstrate the achievable gains of the new communication approach
▪ Publications and presentations of scientific results, teaching duties

Your qualifications
▪ Above-average university degree in electrical engineering, communications engineering, physics (or similar)
▪ Interest in hardware-related development and thorough knowledge of communications engineering
▪ Software: MATLAB (experience with FPGA programming and LabVIEW desirable)
▪ Familiarity with measuring instruments (oscilloscope, spectrum analyzer, etc.)
▪ Goal-oriented, independent and structured work style

Our offer
▪ Current research topic in a challenging international working environment
▪ Full-time position (E13 TVL) with the possibility of earning a doctoral degree

To apply
Please send us your application by e-mail (jobs.lti@ei.tum.de) with the following documents:
▪ Curriculum vitae, copies of relevant certificates and diplomas, contact information for two references
▪ Short description of your research interests and your motivation for the application
▪ Master thesis and (if available) up to 3 publications

Application deadline: August 8, 2019
For further information see: https://www.ei.tum.de/en/lti/stellenangebote

General Information
TUM is aiming to increase the number of women employees, and applications from women are expressly welcomed. People with disabilities, with essentially the same suitability and qualification, will be preferred. As you apply for a position at the Technical University of Munich (TUM), you provide personal data. Please note our data protection information according to Art. 13 Data Protection Basic Regulation (DSGVO) on the collection and processing of personal data in connection with your application http://go.tum.de/554159. By submitting your application, you confirm that you have taken note of the data protection information of the TUM.

Technical University of Munich
Chair of Theoretical Information Technology
Prof. Holger Boche
Theresienstrasse 90, 80333 Munich
Munich, July 2019

 

The Speech Technology Group of Toshiba Research Europe in Cambridge is looking for exceptional candidates to join our team of researchers, working in automatic speech recognition or statistical dialogue systems. We are looking for candidates with background in signal processing, machine learning, acoustic modelling or expertise in building state-of-the-art systems for ASR or Dialogue. 

The candidate should have a PhD or Masters with equivalent experience in the areas of speech technology related to automatic speech recognition, statistical dialogue modelling, machine learning or a related field (Post-doctoral/industrial experience is beneficial).  The candidate has good programming skills with Python and/or C/C++ and proficient with Unix/Linux. Experience with speech and/or machine learning toolkits, e.g. Kaldi, TensorFlow, PyDial, PyTorch, etc. would be beneficial.

For more information please visit: https://www.toshiba.eu/eu/Cambridge-Research-Laboratory/Speech-Technology or alternatively send your CV and covering letter to: stg-res-jobs@crl.toshiba.co.uk

The selected candidate will work in the area of seismic data processing applied to the definition of water masses (seismic oceanography - Inversion). It will also act in the evaluation of the data received and in the preparation and realization of the cruises to obtain shallow seismic data in Brazilian waters and data analysis. It is expected to produce technical reports and scientific papers from the research group.

Requirements: Knowledge of signal processing and programming in computer language (eg MATLAB, Phyton or C ++). Knowledge in seismic inversion is desirable.

Send school history, doctoral thesis and Curriculum Vitae until 04/30/2019.

Grant period: 24 months Value of the scholarship: R$ 6,916.42

 

We have 2 PhD Positions open in Distributed Statistical Learning in IoT with Adversarial Environments

Job Description

In the emerging paradigms of cyberphysical systems (CPS) and internet-of-things (IoT), large quantities of data are constantly collected by numerous sensors that are often geographically dispersed or, to make the matters even more challenging, mobile. This makes concentrating the data at a central processing hub unfeasible due to constraints imposed on the network infrastructure, e.g., the energy budgets of the sensors, as well as the capacity of the communication channels, and security requirements. Thus, distributed processing of data over networks of machines/agents is essential for solving inference problems related to many CPS/IoT-based applications.

Current methods for distributed inference and learning are not adapted for operation in IoT systems with malicious adversaries, vulnerable to data falsification and susceptible to privacy leakage. The goal of this project is to develop distributed signal processing and machine learning algorithms that preserve privacy and are resilient to malicious disturbances, while still maintaining the operational goal of the IoT system, i.e., to effectively convert the data collected by myriads of agents/sensors into actionable intelligence.

Qualification requirements

 We seek two highly-motivated individuals who have

• strong background in mathematics and signal processing, and a research-oriented master thesis in a related field, e.g., statistical signal processing, information theory, statistical machine learning, multi-agent networked systems, applied mathematics, or optimization
• experience with programming
• good written and oral English language skills

Publication activities in the aforementioned disciplines will be considered an advantage but is not a requirement.

Salary and conditions

PhD candidates are remunerated in code 1017, and are normally remunerated at gross from NOK 449 400 before tax per year. From the salary, 2 % is deducted as a contribution to the Norwegian Public Service Pension Fund.

Application submission

For more information on the application submission and a detailed list of required documents, please follow the link Distributed Learning in IoT with Adversarial Environments.

Many applications generate large data sets from which information needs to be extracted. The emerging field of structured data science extends signal processing to data science. 

Context

Retrieving useful information out of large data sets is receiving an increasing amount of attention these days. Emerging applications like autonomous driving, the square kilometre array for radio astronomy, biomedical sensing systems, the internet-of-things with millions of users and sensors, all generate enormous amounts of data and it is not always clear how to gather, process, and analyze that data in an efficient and rigorous manner. Data science provides a solution to this problem. It basically yields a set of tools for data mining, data cleansing, machine learning and data analysis. 

While these tools can tackle a wide variety of problems, computer science approaches often ignore the structure that is present in the problem due to the physics. This structure could come from the prior knowledge of the model that generates the data (e.g., radio frequency channel models, biomedical signal models, diffusion models), or it could directly relate to the structure in the data (e.g., space-time, sparsity, network/graph data). Taking such structure into account will aid many of the existing data science tools, making them easier to interpret and simpler to implement. This field of structured data science is shaped by the nontrivial interplay between conventional signal processing and conventional data science. The goal is to illuminate and explore this interplay and apply it to the earlier mentioned applications.

Requirements

The opening for an Assistant Professor at TU Delft is intended to further develop this area. A background in statistical signal processing/modelling and the ability to apply this to data science/machine learning is required. Generally we search for candidates with a strong signal processing background complementary to the expertise that is already present in the CAS group. 

The candidate will also be involved in teaching and e.g. develop new courses on structured data science and machine learning for Electrical Engineering students.

While this position is defined as a tenure-track Assistant Professor position, excellently qualified but more senior researchers are also invited to apply.

Candidates should have (1) a PhD degree in Electrical Engineering or a closely related disciplne, with outstanding academic credentials, (2) several years of working experience as a Postdoctoral Researcher in an academic institution, and (3) the ambition to be a future scientific leader in the mentioned area.

Please announce your interest to Mrs. Minke van der Put (M.J.vanderPut@tudelft.nl) by submitting your CV, cover letter and contact details. Clearly indicate the related area of interest (i.e., structured data science), as this opening is part of a wider search for new faculty.

Contact Prof. Geert Leus for informal information. 

 

 

Open ETH-FDS Postdoctoral Fellow positions in Foundations of Data Science

ETH Foundations of Data Science (ETH-FDS) is a new cross-departmental initiative at ETH Zurich, starting on 1 January 2019. Its main focus is research-oriented in the area of foundations of data science, at the intersection between information sciences, machine learning and statistics.
We invite applications for ETH-FDS Postdoctoral Fellow positions in Foundations of Data Science.

The positions are for two years. We offer an attractive environment across different core areas in foundations of data science. Besides developing independent research, the duties also include a light teaching load. The starting date is flexible. The salary is according to the standard salary scale for postdoctoral fellows at ETH Zurich.

Your application should include the following documents:

• curriculum vitae, including a list of publications
• preferred host at ETH Zurich (One to three faculty members at ETH Zurich with whom you want to primarily work with.)
• short research statement (one to at most two pages)
• three names of references (no letters need to be submitted).

Applications can be submitted via https://www.math.ethz.ch/the-department/open-positions.html#fds-postdoc .

The deadline for applications is 28 February 2019 (but applications can be sent until the positions are filled).

For more information and contact, please refer to our ETH-FDS website, https://www.math.ethz.ch/sfs/research/fds.html.

We look forward to your application!

Prof. Peter Bühlmann
Director
ETH Zurich
Seminar for Statistics

The Communication Systems Division of the CTTC is searching for interested candidates in a Researcher position for its Advanced Signal and Information Processing (ASIP) Department.

The ASIP Department conducts fundamental and applied research on signal processing and communications, including algorithmic development, theoretical analysis and hardware development. For more information about the department, please refer to http://systems.cttc.es/advanced-signal-and-information-processing/. The candidate will join our team and work on the application of machine learning techniques in wireless communications. The candidate is expected to have a strong background in the following specialization areas of interest: Signal Processing for Communications, Machine Learning, Big Data Analytics and Processing. The applicant is expected to carry out innovative research on machine learning and signal processing for communications, particularly on radio and cellular communications. Proven experience in coordination/participation in European and other research projects will be highly valued. Proficiency in Matlab and Python will also be valued.

QUALIFICATIONS AND EXPERIENCE

Applicants for Researcher positions must hold a Ph.D. degree in telecommunications, computer science, electrical engineering, or related fields; be capable of conduct independent research and be highly motivated to work in a collaborative environment interacting with researchers as well as technology transfer staff; have excellent track publication record and capacity of attracting competitive funds.. English proficiency is required. Research and industrial work experience, management and participation in international and national R&D projects,  and preparation of research grant proposals such as EC funded programs, is all highly appreciated.

 CONDITIONS

The position is temporary (investigador interino, according to the Spanish national law), with perspective to become permanent. The salary will be determined according to qualifications, work experience and budget availability. Interested candidates should send their curriculum vitae, including list of publications, scanned copies of the obtained degree titles and a cover letter stating the motivation and suitability of the candidate. They should also provide the names and addresses of at least two referees. These documents should be sent in PDF format through this online application. CVs and any other information gathered during this process will be handled confidentially.

CTTC

Centre Tecnològic de Telecomunicacions de Catalunya (CTTC), in Castelldefels – Barcelona, is a growing and well-funded research institution fostering excellence and diversity. CTTC offers a highly international environment at an exceptionally attractive location. As a research center in telecommunications technologies CTTC provides a fertile environment for research cooperation and innovation between different disciplines.

CTTC seeks to increase the number of women in those areas where they are underrepresented and therefore explicitly encourages women to apply.

CTTC is committed to increasing the number of individuals with disabilities in its workforce and therefore encourages applications from such qualified individuals.

Application Site: http://www.cttc.es/apply/?id=11095

Development of new optical transmission methods based on nonlinear Fourier transform.

Applications are invited for a three year prestigious Postgraduate Studentship (leading to a PhD) as MSCA Early Stage Researcher, supported the School of Engineering and Applied Science through MSCA ITN European Industrial Doctorates project FONTE, to be undertaken within the Aston Institute of Photonic Technologies (AIPT) [http://www.aston.ac.uk/eas/research/groups/photonics/] at Aston University (Birmingham; UK).

The successful applicant will join an established experimental group working on the applications of the nonlinear Fourier transform signal processing method for the fibre nonlinearity mitigation and the development of the new generation of extra-high-capacity optical networks and related concepts. Secondments: The studentship is offered in collaboration with world-leading industrial unit: Nokia Bell Labs (NBL), Stuttgart, Germany (no less than 18 months at NBL). The project research time and trainings will be equally split between AIPT and NBL. Close collaboration and visits to other three FONTE partners, Technical University of Denmark, Telecom ParisTech (France), and Technical University of Delft (the Netherlands), will be carried out along the project. The position is available to start no later than May 2019 (subject to negotiation) .

Salary
The successful candidates will be employed on a full-time basis with a competitive salary in accordance with the Marie Sklodowska-Curie Actions regulations for Early Stage Researchers (ESRs) and the personal circumstances of the applicant. The successful candidate will receive a financial package consisting of MSCA living allowance and mobility allowance, together £32,750 pa. Eligible candidates will also receive an additional family allowance according to the rules of the MSCA.

PhD studentship bursary
This studentship includes a fee bursary to cover the home/EU fees. Applicants from outside the EU may apply for this studentship but will need to pay the difference between the ‘Home/EU’ and the ‘Overseas’ tuition fees, the difference currently being £12,005 pa in 2017/18. Confirmation that this funding support is in place for the full duration of the PhD studentship will be required as part of the application process

Background of the Project
Nonlinear transmission effects in optical fibre are now a major limiting factor in modern fibre-optic communication systems. Nonlinear propagation effects make optical fibre channels very different from traditional linear communications channels such as wireless or copper cables. There is a clear need for radically different methods for the coding, transmission, and processing of information that take the nonlinear properties of the optical fibre into account. The nonlinear Fourier transform (NFT) that is to be used in place of the conventional Fourier transform, offers new opportunities for the development of fundamentally novel engineering techniques for the coding, modulation, transmission, and processing of information in optical fibre channels. The student will work on the theoretical development and experimental verification of new coding and modulations techniques for NFT-based optical transmission systems under the supervision of world-class mentors: Prof. S. Turitsyn (AIPT, main supervisor), Drs Y. Prylepskiy (AIPT), H. Buelow (NBL), and M. Yousefi (TPT). FONTE ESRs will benefit from cross-disciplinary joint supervision by world experts in optical communication in academia and industry.

Person Specification
FONTE is looking for candidates with exceptional skills in signal processing, optical communication or applied mathematics. Preferred skill requirements include experience in experimental work, knowledge of scientific programming and computing, physical optics, communications. Knowledge in differential equations, mathematical physics, numerical analysis, information and communication theory, or machine learning is an asset. Applicants with a Master of Science degree in Electrical Engineering, Applied Mathematics, Physics, or equivalent, are especially encouraged to apply. The successful applicant should have a first class or upper second class honours degree or equivalent qualification in engineering or physics.

For informal enquiries about this project and other opportunities within the AIPT, contact Prof. Sergei Turitsyn by email: s.k.turitsyn@aston.ac.uk

If you require further information about the application process please contact the Postgraduate Admissions team at seasres@aston.ac.uk

Additional Requirements

1. Academic Entry Requirements
You should have been awarded, or expect to achieve, a first or upper second class Honours degree or equivalent qualification in engineering or physics. Preferred skill requirements include experience in experimental work, knowledge of scientific programming and computing, physical optics, communications. If your qualifications are from an overseas institution please provide transcripts of the marks you have already achieved with your application.

2. English language
For applicants from non-English speaking countries, it is necessary to have taken either the Test of English as a Foreign Language (TOEFL) or the British Council IELTS test (taken no more than two years before the start date of your course). Minimum requirements are: TOEFL IBT: 93 (23 in Writing, 19 in Speaking, 18 in Reading and 19 in Listening) IELTS: 6.5 (6.0 in Writing Speaking, Reading and Listening). Pearsons English language test: 63 with no less than 57 in each band

Further information can be found at http://www.aston.ac.uk/eas/research/prospective-research-students/how-to-apply/

3. MSCA Eligibility
Applicants must be Early Stage Researchers (ESR), i.e. be in the first four years (full-time equivalent research experience) of their research careers and have not been awarded a doctoral degree. Full-time equivalent research experience is measured FROM the date when the researcher obtained the degree entitling him/her to embark on a doctorate (either in the country in which the degree was obtained or in the country in which the researcher is recruited) – even if a doctorate was never started or envisaged. Research Experience is measured TO the first day of the FONTE employment contract of the researcher.

4. MSCA Mobility
Researchers may not have resided or carried out their main activity (work, studies, etc.) in the UK for more than 12 months in the 3 years immediately before the recruitment date.

Interested candidates should contact Prof Sergei Turitsyn [s.k.turitsyn@aston.ac.uk]  in the first instance.