Machine Learning for Signal Processing

Position description: The Signal Acquisition Measurement and Processing Lab at the Technion welcomes applications for a postdoctoral position with focus on deep learning. Specifically we are interested in Ph. D. graduates with profound and solid knowledge in both signal processing and modeling and deep learning techniques to work on projects which are in the interface between the two approaches. Good theoretical and abstract thinking is required. The balance of work between theory and practice will vary on project-basis, and a successful candidate should be proficient in both aspects. Candidate should have an excellent publication record in signal processing and/or machine learning journals. Excellent written and presentation skills in English are an advantage.

Position description:

The Signal Acquisition Measurement and Processing Lab at the Technion welcomes applications for a postdoctoral position with focus on deep learning. Specifically we are interested in Ph. D. graduates with profound and solid knowledge in both signal processing and modeling and deep learning techniques to work on projects which are in the interface between the two approaches. Good theoretical and abstract thinking is required. The balance of work between theory and practice will vary on project-basis, and a successful candidate should be proficient in both aspects. Candidate should have an excellent publication record in signal processing and/or machine learning journals. Excellent written and presentation skills in English are an advantage.

 Contact Details:

For more details please visit Prof. Eldar’s website. 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

The Idiap Research Institute together with a global industry partner, leader in Consumer Electronics, invite applications for two post-doctoral positions in speech and speaker recognition for HMI devices. The positions are funded for two years by the Swiss Commission for Technology and Innovation (CTI), enabling a collaboration between Idiap and an innovative product company.

The successful candidates will work with Dr. Philip N. Garner, and/or Dr. Petr Motlicek in Idiap's Speech and Audio Processing group, engaged in world-class research in speech processing. Exceptionally qualified candidates can also be considered for a longer-term Research Associate position.

To apply, follow the links at http://www.idiap.ch/education-and-jobs/job-10232

Description

In recent years, the state of the art in speech and speaker recognition has been dominated by deep learning. Such technology is typically highly parametric; training can require significant CPU or GPU resources. The goal of the project is to investigate the application of the state of the art to the more limited resources of consumer-grade embedded systems which operate in combination with cloud services.

We envisage three related research threads:

1. Parameter reduction, in which we will apply sparsity and relevance constraints to train networks that function using as few parameters as possible.

2. Smart handover, in which we will assess the complexity of voice commands to optimise workload between local devices and cloud-based services.

3. System combination, in which we will build on the commonality between technologies for multilingual speech recognition, keyword spotting and speaker recognition to create a single system with multiple capabilities.

The successful candidates will work at Idiap in Martigny, but in close collaboration with the partner’s R&D team based in Switzerland. The project is a unique combination of applied science and academic research expected to yield both reference designs and academic publications.

Profile

Candidates should have either or both of:
1. A strong background in engineering, mathematics or a related discipline, along with the associated familiarity with modern distributed programming environments and languages such as C++, Python and Perl.
2. An exceptional academic record and a clear aptitude for creative (and independent) research in a related discipline.
In either case, familiarity with speech processing tools such as Kaldi and deep learning toolkits such as Torch will be a distinct advantage. Although a PhD is normally a prerequisite for a post-doctoral position, candidates without a PhD may be considered in exceptional cases.

Timescale

All positions are offered on a one-year basis with the possibility of renewal based on funding and performance. The starting salary will be 80,000 CHF/year. Starting date could be immediate, but otherwise as soon as possible in 2018.

Idiap is an independent, not-for-profit, research institute recognized and funded by the Swiss Federal Government, the State of Valais, and the City of Martigny.

Idiap offers competitive salaries and conditions at all levels in a young, high-quality, dynamic, and multicultural environment. Idiap is an equal opportunity employer and is actively involved in the "Advancement of Women in Science" European initiative. The Institute seeks to maintain a principle of open competition (on the basis of merit) to appoint the best candidate, provides equal opportunity for all candidates, and equally encourage both genders to apply.

Idiap is located in the town of Martigny in Valais, a scenic region in the south of Switzerland, surrounded by the highest mountains of Europe, and offering exceptional quality of life, exciting recreational activities, including hiking, climbing and skiing, as well as varied cultural activities. It is within close proximity to Lausanne and Geneva. Although Idiap is located in the French part of Switzerland, English is the official working language. Free French lessons are also provided on a complimentary basis.

For frequently asked questions (FAQs) about living in Switzerland, please go to http://www.idiap.ch/en/faq

November 2017

Postdoctoral research position:

Acoustic cough detection and processing for healthcare

A postdoc position focussing on the automatic detection, analysis and classification of coughing in unconstrained audio for healthcare monitoring and disease screening is available in the Digital Signal Processing Group of the Department of Electrical and Electronic Engineering at the University of Stellenbosch, South Africa.

The project will involve the development of machine learning algorithms that are able to automatically distinguish and characterise coughing in a noisy environment, with an emphasis on the monitoring of tuberculosis. The project will also include the compilation of data corpus and collaboration with medical practitioners.

Specific project objectives include the gathering of the acoustic data, setting up and managing the annotation process, developing automatic detection and classification systems using the gathered data, and producing new and original research into how best to automatically detect and classify coughing in a difficult acoustic environment.

Applicants must hold a PhD (preferably obtained within the last 5 years) in the field of Electronic/Electrical Engineering, Information Engineering, Computer Science, or other relevant discipline. Suitable candidates must also have practical and research experience in a relevant machine learning specialisation such as automatic speech or speaker recognition or sound event detection. The candidate should have an excellent background in statistical modelling, signal processing, and/or audio analysis. Applicants should also have proven prior experience in data compilation, have good programming skills and be able to use high level programming languages for developing prototype systems. Finally, candidates must have excellent English writing skills and have an explicit interest in scientific research and publication.

The position will be available for one year, with a possible extension to a second year, depending on progress and available funds.

Applications should include a covering letter, curriculum vitae, list of publications, research projects, conference participation and details of three contactable referees and should be sent as soon as possible to: Prof Thomas Niesler, Department of Electrical and Electronic Engineering, University of Stellenbosch, Private Bag X1, Matieland 7602. Applications can also be sent by email to: trn@sun.ac.za. The successful applicant will be subject to University policies and procedures.

Interested applicants are welcome to contact me at the above e-mail address for further information regarding the project.

Experience IT – Intuitive Technology: this principle guides our work at the European Media Laboratory. We are an IT enterprise, based in Heidelberg, Germany, focusing on the automatic conversion of speech into text for a variety of markets. Speech technologists and IT specialists research, develop and use state-of-the-art large-vocabulary automatic speech recognition technologies, including deep learning, to convert spoken audio into structured textual data and actions. Our products currently comprise server-based speech recognition for speech analytics, media transcription, voice messaging, voice search and dictation as well as on-device language model and grammar-based speech recognition solutions for house control, car control and smartphones. For further details on our activities please have a look at our “Best-Practice”-Examples.

For our research and development projects we hire at the earliest possible date experienced

Technologists (m/f) for Speech Processing Systems

meeting the following criteria:

• Hands-on experience in developing state-of-the-art technologies for speech recognition and / or language understanding systems.
• Experience in evaluating and tuning speech recognition and understanding systems.
• Fluency in programming languages such as C++, Java, and Python for Linux, Windows, Android or iOS.
• Degree in computer science, mathematics, computational linguistics or related disciplines.

Successful candidates should have several years of applied and theoretical experience in several of the areas mentioned; a PhD or an equivalent level of applied expertise would be helpful. All positions require an application-oriented perspective and a willingness to listen to and act upon customers’ concerns.

Interested? Please send us your written application with the subject "Job advertisement EML/05/2017" as soon as possible but no later than July 15th, 2017 to the following address:

Prof. Dr. Andreas Reuter, Managing Director, EML European Media Laboratory GmbH, Berliner Straße 45, 69120 Heidelberg or by E-Mail to Dr. Siegfried (Jimmy) Kunzmann (bewerbung@eml.org), Manager R&D.

Job Opening – Darmstadt (Frankfurt area)/Germany, December 2016

AGT is all about striving for the best Analytics for the Internet of Things!

Our teams are professional and fearless – our working environment is energized, sweeping and demands use of cutting edge technology. We are never behind. Out of the box thinking and creativity in everything we do. Being always in search of new ideas turning into great new features and products, we would love to meet and welcome team members joining the ride and driving us forward. We are looking for

Senior Data Scientists (General Machine Learning)

Senior Data Scientists (Wearable Analytics)

Senior Data Scientists (Audio Analytics)

Senior Data Scientists (Emotion Recognition)

AGT is passionate about creating a unique analytics engine to answer highly valuable business questions across various industries. Our focus is on innovative and new technologies for Internet of Things, specifically for sports and entertainment. We provide the opportunity to drive ideas from conception to products which are deployed in the market. You will be given the opportunity to work directly with our customers and partners to solve their data-driven problems and needs where you will be working with large as well as unique and complex data sets from traditional data sources and from the rapidly growing world of IoT sensors.

With your PhD in machine learning or signal processing you will join a larger team of like-minded and talented people, eager to squeeze out informational value from various data sources and explore new ways. Your contributions will end up in exciting products in the domain of sports and entertainment and you will be given the opportunity to work on a variety of tasks and develop your skills in many area ranging from new and exciting analytics technologies to collaboration with agile development teams, Product Management, Marketing and Sales.

We will provide you with an environment fostering the autonomy of data scientists and a good mix between coding, conceptualization and customer engagement.

The Neural Processing and Control Lab (NeuralPC Lab) at the University of Rhode Island (URI), Department of Electrical, Computer, and Biomedical Engineering (ECBE) has two PhD position openings in the field of neural signal processing and Brain-Computer Interface (BCI) systems. The position offers a competitive stipend and tuition waiver for the graduate assistants.  The nature of this position will provide the graduate students with opportunities to work on multidisciplinary collaborative projects.

We are seeking highly motivated and talented graduate research students whose research interests lie at the intersection of neural engineering, cognitive neuroscience, and control systems. Our current lab’s projects include developing Hybrid BCI systems, neural signal analysis of patients with different types of neurological impairments including patients with disorders of consciousness (DOC), epilepsy, Schizophrenia, and Parkinson’s disease (PD) with different brain imaging modalities of invasive and non-invasive recordings. The successful candidates must have master’s degree in electrical engineering or biomedical engineering, background in neural engineering, signal processing, machine learning algorithms, and extensive programming experience with Matlab. Background in BCI and control systems, cognitive neuroscience, and other programming languages such as C++ are desired but not mandatory.

The ECBE department, offers programs in BS, MS, and PhD degrees. URI’s College of Engineering offers innovative undergraduate and graduate programs with comprehensive doctoral research. The main campus is located in Kingston, an established, family-friendly, small community only five miles from Narragansett Bay and the Atlantic Ocean. Kingston lies in close proximity to popular tourist destinations, like Narragansett, Boston, and New York, yet still retains its small town feel. The weather is tempered compared to nearby states due to close proximity to the Atlantic Ocean. Living in Rhode Island offers an array of outdoor activities and close proximity to major metropolitan areas for a quick getaway.

Applicants should submit a cover letter, resume, a brief summary of the current and proposed research, GRE, TOEFL/IELTS (for international students only), official/unofficial master and bachelor academic transcripts, and three letters of recommendation to Dr. Yalda Shahriari (Yalda_shahriari@uri.edu) preferably before Dec 15^th. Please send all your documents as a single PDF file. Applications will be considered until the positions are filled.

Yalda Shahriari, Ph.D.
Assistant Professor
Department of Electrical, Computer & Biomedical Engineering, University of Rhode Island
Affiliate Member of University of California, San Francisco
Affiliate Member of George and Anne Ryan Institute for Neuroscience
Office: A-102, Kelley Annex, 4 East Alumni Ave, Kingston, RI 02881
Phone: 401 874 5368

Web: http://egr.uri.edu/ele/meet/yalda-shahriari/

Experience IT – Intuitive Technology: this principle guides our work at the European Media Laboratory. We are an IT enterprise, based in Heidelberg, Germany, focusing on the automatic conversion of speech into text for a variety of markets. Speech technologists and IT specialists research, develop and use state-of-the-art large-vocabulary automatic speech recognition technologies, including deep learning, to convert spoken audio into structured textual data and actions. Our products currently comprise server-based speech recognition for speech analytics, media transcription, voice messaging, voice search and dictation as well as on-device language model and grammar-based speech recognition solutions for house control, car control and smartphones. For further details on our activities please have a look at our brochure “EML Voice - Speech Technology Today” (http://www.eml.org/downloads/PDF/EML_Voice_Heft_2014_web_small.pdf").

For our research and development projects we hire at the earliest possible date experienced

Technologists (m/f) for Speech Recognition Systems

meeting the following criteria:

• Hands-On experience in developing state-of-the-art speech recognition decoders, language models or acoustic models.
• Experience in evaluating and tuning speech recognition systems.
• Fluency in programming languages such as C++, Java, and Python for Linux, Windows, Android or iOS.
• Degree in computer science, mathematics, computational linguistics or related disciplines.

Successful candidates should have several years of applied and theoretical experience in several of the areas mentioned; a PhD or an equivalent level of applied expertise would be helpful. All positions require an application-oriented perspective and a willingness to listen to and act upon customers’ concerns.

You will find a demanding as well as a stimulating working environment.

Interested? Please send us your written application with the subject "Job advertisement EML/07/2016" as soon as possible but no later than November 15th, 2016 to the following address:

Prof. Dr. Andreas Reuter, Managing Director, EML European Media Laboratory GmbH, Berliner Straße 45, 69120 Heidelberg or by E-Mail to Dr. Siegfried (Jimmy) Kunzmann (bewerbung@eml.org), Manager R&D.