Machine Learning for Signal Processing

The Signal Processing research group at the Universität Hamburg (http://uhh.de/inf-sp) is hiring a postdoctoral researcher for 33 months for the project "Crossmodal Processing of Audio-Visual Signals".

Please find the full job announcement with all details here.
https://www.inf.uni-hamburg.de/en/inst/ab/sp/job-offer.html

Specific Duties:
The candidate will work in the Signal Processing group and will do research on modern methods for speech, audio, and audio-visual processing. The focus of the group is on developing novel methods for processing speech signals with applications in speech communication devices such as assistive listening, mobile telephony, and voice-controlled assistants. Typically, the performance of these devices drops drastically when interfering noise sources are present. To mend this undesired behavior, noise reduction is applied.
The goal of the successful candidate is to improve noise reduction systems by incorporating visual information captured by a camera. For this, modern methods from signal processing and machine learning are to be applied. Besides developing new concepts and implementing new algorithms, the typical tasks include experiments to test the methods, writing scientific publications, and traveling to conferences and workshops to present the work. We are interested in a highly motivated person who is interested in working with us on cutting edge research in a pleasant working atmosphere.

Are you an early-career researcher who enjoys finding innovative solutions to unmet clinical needs and translating deep learning in medical image analysis to the clinic? Do you have a background in medical image computing and experience with working collaboratively with clinicians and clinical image databases? Do you have a passion for developing statistical deep Bayesian methods for medical image analysis? Are you ready to think out-of-the-box, innovate and find solutions to challenging problems?

The Centre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), within the Faculties of Engineering and Medicine & Health, involves various academics and their research groups. CISTIB focuses on algorithmic and applied research in the areas of computational imaging, and image-based computational physiology modelling and simulation. CISTIB contributes in different areas of medical image computing and image-based biomechanical and computational physiology modelling. CISTIB works in close cooperation with clinicians from various research centres from the University of Leeds and the academic hospitals of the Leeds Teaching Hospital Trust Foundation, the largest NHS Trust of the UK.

Clinical areas where CISTIB members have contributed to and made substantive innovations in the field are focused around the cardiovascular, musculoskeletal and neural systems, where they have developed diagnostic and prognostic quantitative image-based biomarkers and methods and systems for interventional planning and guidance. The centre hosts academic members from the University of Leeds and Research Fellows, Research Associates, PhD Students and Scientific Software Developers forming a cross-disciplinary team committed to clinical translation of their innovations.

You will be part of the EPSRC funded BIANDA project and develop a full probabilistic atlas to accurately evaluate bi-ventricular motion abnormalities by integrating cardiac magnetic resonance (CMR) and metadata from a large population. The motion will be modelled as the spatiotemporal (3D+t) sequence of the heart shapes across the full cardiac cycle, extracted from cine CMR images. The atlas will be a Bayesian recurrent model that, given a sequence, it will predict a probabilistic distribution function (pdf) for the next status of the heart. More importantly, the pdf will be conditioned on the patient's metadata. The atlas will be derived from the UK Biobank CMR study aiming to scan n>100,000 patients by 2022. The training of the atlas will be pursued as the new releases of the data sets from the UK Biobank becomes available. The PI has an extensive experience in developing Bayesian and non-Gaussian statistical atlases from shapes and you will have the opportunity to closely teamwork with him. He has established collaboration with the clinical advisor for this study and has full access to the CMR data sets.

This role is fixed term for 18 months, and the salary is in the range £33,199 - £39,609p.a.

For more details and to apply, please visit http://jobs.leeds.ac.uk/engcp1096

Title:  Machine Learning/Speech research internship  @ Seattle, WA

Time: Summer/Fall 2019

About You

A wiliness to be a better you on a day by day basis.

About Us:

We enable hundreds of millions of commercial and social interactions among our users, between consumers and merchants, and among businesses every day though speech.

What You’ll Do

Develop and refine algorithms to improve speech system performance under adverse conditions such as noise, channel, and accent mismatch. Machine Learning, Speaker ID, Audio fingerprinting/ Audio watermark background is highly welcome. 

Skills You’ll Need

MSc/PhD candidate in Engineering, Computer Science or a related field

Proficiency in speech enhancement and robust acoustic feature engineering is a plus

Experience with speech system performance improvements under adverse condition is a plus

Speaker/Language/Accent/Emotion Identification is a plus

Speaker Recognition Anti-spoofing is a plus

Deep learning (DNN, CNN, LSTM)

Familiarity with C++, Python, Matlab, Bash shell

Familiarity with ASR toolkits (e.g., Kaldi), DNN toolkits (Theano)

Solid publication record

Application Deadline:  Porcessed on a rolling basis

Contacts:

g.liu@alibaba-inc.com

Apply here: https://www.kuleuven.be/personeel/jobsite/jobs/55004282?hl=en&lang=en

Responsibilities

This job opening covers a research position (minimum 2 years) at the STADIUS group of the Department of Electrical Engineering (ESAT) of KU Leuven (Belgium) for a postdoctoral researcher in the frame of an ERC project on next-generation wearable neuro-technology and neuro-sensor networks.  The candidate will design novel adaptive neural decoding algorithms, amenable to low-power wearable neural sensors with constrained energy resources. The candidate may also be involved in the guidance and support of PhD students within the lab.

Profile

Candidates should preferably have experience with setting up EEG-based BCI experiments, and should have a good theoretical knowledge and insight in state-of-the-art signal processing and machine learning algorithms. Experience with neural decoding, EEG data collection, and/or brain-computer interfaces is a strong plus. Additional research/educational experience in any of the following topics is a plus:   - Adaptive filtering - Component analysis theory and application (PCA, ICA, IVA, CCA, …) - Machine learning (deep or not) - Multi-channel signal processing and spatial filtering - (Blind) source separation - Sensor array processing (beamforming, detection, …) - Distributed signal processing - Optimization theory (convex or non-convex)   Candidates should have co-authored at least 3 papers in high-quality engineering journals with a good impact factor in a field related to the abovementioned topics.    Candidates should be motivated, independent, critical, and should have strong team-player skills. Excellent proficiency in the English language is also required, as well as good communication skills, both oral and written.

Offer

- An exciting interdisciplinary research environment at KU Leuven, Europe’s most innovative university (Reuters: https://www.reuters.com/innovative-universities-europe-2018/profile?uid=1 ) - The opportunity to improve leadership skills (including supervising PhD students). - The possibility to participate in international conferences and collaborations - A 2-year contract with a competitive monthly stipend (with the possibility to extend it beyond 2 years).   More info: https://www.kuleuven.be/personeel/jobsite/jobs/55004282?hl=en&lang=en

Two Postdoctoral Researcher/Project Researcher positions in speech processing

The University of Eastern Finland, UEF, is one of the largest multidisciplinary universities in Finland. We offer education in nearly one hundred major subjects, and are home to approximately 15,500 students and 2,500 members of staff. We operate in Joensuu and Kuopio. In international rankings, we are ranked among the leading universities in the world.

The Faculty of Science and Forestry operates on the Kuopio and Joensuu campuses of the University of Eastern Finland. The mission of the faculty is to carry out internationally recognised scientific research and to offer research-education in the fields of natural sciences and forest sciences. The faculty invests in all of the strategic research areas of the university. The faculty’s environments for research and learning are international, modern and multidisciplinary.  The faculty has approximately 3,800 Bachelor’s and Master’s degree students and some 490 postgraduate students. The number of staff amounts to 560. http://www.uef.fi/en/lumet/etusivu

We are now inviting applications for 

two Postdoctoral Researcher/Project Researcher positions in speech processing funded by the Academy of Finland at the School of Computing, Joensuu Campus.

• One position in machine learning for speaker modelling (e.g. speaker verification, voice anti-spoofing, voice conversion, text-to-speech, or similar)
• One position in perceptual and/or acoustic speaker characterization (e.g. phonetics/linguistics, speech modelling, statistical methods)

Both positions are filled in the Academy of Finland funded NOTCH research project (NOn-cooperaTive speaker CHaracterization), led by Associate Professor Tomi H. Kinnunen. The project aims at advancing the state-of-the-art in automatic speaker verification (defence) and voice conversion (attack) under a generic umbrella of non-cooperative speech, whether being induced by spoofing attacks, disguise, or other less expected intentional voice modifications. The NOTCH project applies multi-disciplinary research methods. The ideal candidate for the first position will have a background in machine learning or signal processing for speaker modelling and characterization. You may have a background in recognition, conversion or synthesis methods, as long as you are seasoned in state-of-the-art machine learning theory and practice (especially deep learning). The ideal candidate for the second position will have a background in acoustic-phonetic or perceptual methods for speaker characterization and will be fluent in devising novel statistical analysis methods such as linear mixed effect models. For both positions, multi-disciplinary thinking and willingness to contribute to both themes is considered a plus.

The Computational Speech Group of the School of Computing (https://www.uef.fi/web/speech/) , formed officially in 2018, works in the facilities of Joensuu Science Park, provides access to a modern research infrastructure and is a strongly international working environment. We are a group of dedicated individuals who do not want to follow a linear research path – we keep our mind open to high-risk new directions and collaborations. We hosted the Odyssey 2014 conference, were a partner in the H2020-funded OCTAVE project, and are known as a co-founder of the Automatic Speaker Verification and Countermeasures (ASVspoof) challenge series (http://www.asvspoof.org/). Joensuu, a friendly city “in the middle of KNOWhere” (as one of UEF’s slogans say) of about 115,000 inhabitants, is compact and contains all the necessary services within walking distance, with low living expenses and excellent opportunities for many outdoor activities. Despite its remote location, Joensuu is very international thanks to many of UEF’s international collaboration programmes and a vibrant student community.  

A person to be appointed as a postdoctoral researcher shall hold a suitable doctoral degree that has been awarded less than five years ago. If the doctoral degree has been awarded more than five years ago, the post will be one of a project researcher. The doctoral degree should be in spoken language technology, electrical engineering, computer science, machine learning or a closely related field. Researchers finishing their PhD in the near future are also encouraged to apply for the positions. However, they are expected to hold a PhD degree by the starting date of the position. We expect strong hands-on experience and a creative, out-of-the-box problem solving attitude. A successful applicant needs to have an internationally proven track record in topics relevant to the project he or she applies to.

English may be used as the language of instruction and supervision in these positions.

The positions will be filled from earliest April 1, 2019 for a minimum period of 12 months. The continuation of the positions will be agreed separately. The positions will be filled for a fixed term due to them pertaining to a specific project (positions of postdoctoral researcher shall always be filled for a fixed term, UEF University Regulations , Section 31).

The salary of the positions is determined in accordance with the salary system of Finnish universities and is based on level 5 of the job requirement level chart for teaching and research staff (€2,903.61/ month). In addition to the job requirement component, the salary includes a personal performance component, which may be a maximum of 50.0% of the job requirement component. The salary of a postdoctoral researcher is in the beginning around 3,300.00 - 3,500.00 euros.

For further information on the position, please contact (NOTCH): Associate Professor Tomi Kinnunen, email: tkinnu(a) cs.uef.fi, tel. +358 50 442 2647. For further information on the application procedure, please contact: Executive Head of Administration Arja Hirvonen, email: arja.hirvonen(a) uef.fi, tel. +358  29 445 3002.

A probationary period is applied to all new members of the staff.

You can use the same electronic form to apply for both research projects. The electronic application should contain the following appendices:

• a résumé or CV
• a list of publications
• copies of the applicant's academic degree certificates/ diplomas, and copies of certificates / diplomas relating to the applicant’s language proficiency, if not indicated in the academic degree certificates/diplomas
• motivation letter

The application needs to be submitted no later than February 28, 2019 (by 24:00 EET) by using the electronic application form.

Apply here.

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

We design, create and build outstanding experiences by developing and implementing new algorithms at the intersection of audio, voice, DSP, multimodal interfaces and new technologies.    What You’ll Do •  You will research, design, and prototype future Sonos systems and algorithms. •  You will collaborate with Audio Systems Engineering, EE HW, User Experience and various SW teams. •  You will drive innovation and push the boundaries of what we can achieve with human machine interaction and focus on speech and audio. •  You are confident in the state of the art and expertise in your field and you are ready to bring it to the next level. •  You will enable great user experiences by developing new algorithms.    Skills You’ll Need •  MS or Ph.D. in Electrical Engineering, Computer Science, Physics, Acoustics.  •  3+ years of direct audio systems experience in product development or post graduate experience. •  Strong background in DSP, statistical signal processing and machine learning. •  Good mathematical understanding of audio, physics and signal processing. •  Experience in an applied research or advanced development. •  Developed non-trivial audio systems and/or algorithms. •  Proven track record of delivering innovative solutions (products, patents, publications). •  Proven ability of working effectively in complex interdisciplinary environments. •  Proficient in C, C++, MATLAB, and/or Python.  

At the Audio Signal Processing Group, Friedrich-Alexander Universität Erlangen-Nürnberg, Germany, a fully funded postdoc position (100%, funded according to the German public service salary level TVL-E13) is available for a 2-year period from now on, with the possibility of extension subject to continued funding.

We are looking for researchers with an excellent PhD in electrical engineering, computer science, physics, or mathematics. A strong background in statistical signal processing as well as familiarity with state-of-the-art machine learning techniques are expected. Prior experience in speech and audio signal processing is a definite plus. English language proficiency and programming skills in Matlab or Python, and C/C++ are required.

The goal of the project is to advance the development of data-driven techniques for real-time acoustic signal processing tasks, such as system identification, signal enhancement and source separation. Significant results will be presented at leading conferences and published in high-impact journals.  

The University Erlangen-Nuremberg aims at an increase of female staff members and hence encourages qualified women to apply. The application of qualified persons with handicaps is also encouraged.

Please send your application, containing CV, Master's transcript, PhD certificate, motivation letter, electronic copies of up to three relevant publications, and the email addresses of at least two references to walter.kellermann@fau.de at your earliest convenience. Position will be open until filled.

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

Position description: The department of Electrical Engineering at the Technion - Israel Institute of Technology invites researchers for a postdoctoral position in the area of machine learning for healthcare Medical Imaging and automotive radar. The selected candidate will work with Prof. Yonina Eldar at the SAMPL lab in collaboration with clinicians in Israel and USA.

Qualifications: Applicants should have a Ph.D. (or they are about to graduate) in electrical engineering, computer science, or applied mathematics. A strong background in signal processing or computing is required. Excellent English writing skills are an advantage.

Compensation: This is a full-time, one-year, non-tenure-track appointment with possibility of extension subject to satisfactory performance. Funds for conference travel and research expenses will also be provided. Starting date is flexible.

For more details please visit Prof. Eldar’s website: http://webee.technion.ac.il/Sites/People/YoninaEldar/

To submit your application, please send an updated CV with a list of publications, 3 letters of recommendation and a cover letter to yonina@ee.technion.ac.il