Speech and Language Processing

The National Institute on Deafness and Other Communication Disorders (NIDCD) will soon accept applications for a professional track Health Scientist Administrator (HSA) Program Officer with expertise and research experience in data science and cloud computing efforts leveraging “big data” for biomedical research. We anticipate that the vacancy announcement for an HSA Program Officer will be posted on 1/18/22 at http://jobs.nih.gov/globalrecruitment and close on 1/27/22. Salary is commensurate with individual qualifications and professional experience. A full benefits package is available, including retirement, health insurance, life insurance, long-term care insurance, annual and sick leave, and Thrift Savings Plan (401K equivalent). 

The successful applicant will oversee and enhance an extramural research portfolio related to data science, natural language processing, and machine learning. This will include encouraging NIDCD-supported investigators to integrate data collection, storage, analysis, use, and sharing according to FAIR practices. Desired qualifications for candidates include expertise in cloud computing platforms, data repositories, machine learning, and other activities involving significant data science experience. A doctoral degree in engineering, bioinformatics, or other fields with a focus on leveraging cloud-based computing for biomedical research is preferred; individuals at early to mid-career stages are strongly encouraged to apply.

The NIDCD is deeply committed to diversity of thought, equity, and inclusion and encourages applications from qualified women, under-represented minorities, and individuals with disabilities. All qualified applicants will receive consideration without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

Please contact Roger Miller, Ph.D., with questions or interest.

The Department of Computer Science at the University of Texas at El Paso invites applications for two open-rank faculty positions starting Fall 2021 in the areas of Spoken Language Processing, Machine Learning, Computer Systems, or Software Engineering. For details, including required qualifications and application instructions, please visit https://www.utep.edu/employment.  We welcome those working in both core SLT areas and in interdisciplinary areas.  Informal inquiries may be directed to Professor Nigel Ward: nigelward@acm.org.

The AI for Sound project (https://ai4s.surrey.ac.uk/) in the Centre for Vision, Speech and Signal Processing (CVSSP) at the University of Surrey is offering the following PhD studentships in AI for Sound, available from 1 October 2021: (1) Automatic sound labelling for broadcast audio (2) Information theoretic learning for sound analysis (UK applicants) Application Deadline: 1 August 2021 CVSSP also has a number of ongoing PhD studentship opportunities for outstanding PhD candidates in all aspects of audio-visual signal processing, computer vision and machine learning, including for research related to machine learning and audio signal processing. We also welcome enquiries from self-funded and part-funded candidates. For informal enquiries on opportunities related to AI for Sound, please contact Prof Mark Plumbley (m.plumbley@surrey.ac.uk). Further information how to apply below. ----- ** PhD studentship opportunities in AI for Sound project ** (1) Automatic sound labelling for broadcast audio The aim of this project is to develop new methods for automatic labelling of sound environments and events in broadcast audio, assisting production staff to find and search through content, and helping the general public access archive content. The project will undertake a combination of interviews and user profiling, analysis of audio search datasets, and categorisation by audio experts to determine the most useful terminology for production staff and the general public as user groups.

The project will develop a taxonomy of labels, and examine the similarities and differences between each group. The project will also investigate the application of a labelled library in a production environment, examining workflows with common broadcast tools, then integrating and evaluating prototype systems. The project will also investigate methods for automatic subtitling of non-speech sounds, such as end-to-end encoder-decoder models with alignment, to directly map the acoustic signal to text sequences. Working with BBC R&D, the student will develop software tools to demonstrate the results, especially for broadcasting and the management of audiovisual archive data, and benchmark the results against human-assigned tags and descriptions of audio content. Using archive data provided by BBC R&D, the student will engage with audio production and research experts through Expert Panels, and potential end users through Focus Groups. As part of this PhD, you will have the opportunity for close day-to-day collaboration with the BBC as a member of the R&D Audio Team. Application Deadline: 1 August 2021 More information and how to apply: https://www.surrey.ac.uk/fees-and-funding/studentships/automatic-sound-labelling-broadcast-audio (2) Information theoretic learning for sound analysis (Funding Eligibility: UK applicants only) The aim of this PhD project is to investigate information theoretic methods for analysis of sounds. The Information Bottleneck (IB) method has emerged as an interesting approach to investigate learning in deep learning networks and autoencoders. This project will investigate information-theoretic approaches to analyse sound sequences, both for supervised learning methods such convolutive and recurrent networks, and unsupervised methods such as variational autoencoders. The project will also investigate direct information loss estimators, and new information-theoretic processing structures for sound processing, for example involving both feed-forward and feedback connections inspired by transfer information in biological neural networks.

Application Deadline: 1 August 2021 More information and how to apply: https://www.surrey.ac.uk/fees-and-funding/studentships/information-theoretic-learning-sound-analysis ** Other PhD studentships in the Centre for Vision, Speech and Signal Processing (CVSSP) ** CVSSP also has a number of PhD studentship opportunities for outstanding PhD candidates, including for research related to machine learning and audio signal processing. For more information see https://www.surrey.ac.uk/centre-vision-speech-signal-processing/postgraduate-research-study and scroll to "PhD studentship opportunities at CVSSP".

For informal enquiries on opportunities related to AI for Sound, please contact Prof Mark Plumbley (m.plumbley@surrey.ac.uk).

The Signal Processing (SP) research group at the Universität Hamburg in Germany is hiring a Postdoc (E13/E14) "Machine Learning for Speech and Audio Processing".

The general focus of the Signal Processing (SP) research group is on developing novel signal processing and machine learning methods for speech and multimodal signals. Applications include speech communication devices such as hearing aids and voice-controlled assistants. The research associate will do research on novel signal processing and machine learning methods applied to speech and/or multimodal signals. Furthermore the research associate will help establishing degree programs in the data science context.

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

Youtube Demos of our group can be found here.
 

We are looking for a motivated and talented individual to work on a two-year UKRI-funded project in the area of expressive speech synthesis. Follow https://www.jobs.ac.uk/job/CHB468/research-associate-in-speech-synthesis to apply and learn more details about the post.The deadline for submitting applications is July 23, 2021.

The Faculty of Engineering at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) invites applications for a

Tenure Track Professorship for Intelligent Speech Interfaces

(W1 / Assistant Professor)

 at the Department of Computer Science. The professorship is to be filled by the earliest possible starting date, for an initial period of three years. Upon successful evaluation, the appointment will be extended for another three years. FAU offers the long-term perspective of a permanent appointment to a W3 professorship if the requirements of the tenure evaluation are met. The professorship is financed with funds from a Federal and State programme for supporting young researchers at German universities.

We seek to appoint a top early career scientist who will develop outstanding expertise in the field. The aim of the professorship is to set up a chair in computer science as part of a tenure process within the framework of the AI Network Bavaria and the High-Tech Agenda Bavaria (HTA). The successful candidate will have experience in at least one of the areas of automatic speech recognition, dialogue systems, and speech assistance systems and must have a strong background in machine learning. Participation in the computer science, artificial intelligence, medical engineering, and data science degree programmes is expected.

Successful candidates demonstrate initial academic achievements and the capacity for independent research at the highest international standards. You have substantial research experience abroad and/or experience in managing research projects and in raising third-party funding. A university degree and an outstanding doctoral degree as well as a passion for education and pertinent teaching experience are also prerequisites. Candidates who are able and willing to teach in both English and German are desired.

FAU expects applicants to become actively involved in administering academic affairs and in developing strategic initiatives. FAU pursues a policy of intense student mentoring and therefore expects its teaching staff to be present during lecture periods.

FAU offers career development, mentoring and an attractive initial research budget. Based on international standards and transparent performance agreements, FAU ensures a fair tenure track evaluation process.

In its pursuit of academic excellence, FAU is committed to equality of opportunity and to a proactive and inclusive approach, which supports and encourages all under-represented groups, promotes an inclusive culture and values diversity. FAU is a family-friendly employer and is also responsive to the needs of dual career couples.

Please submit your complete application documents (CV, list of publications, list of lectures and courses taught, copies of certificates and degrees, list of third-party funding) online at https://berufungen.fau.de by 30 June 2021, addressed to the Dean of the Faculty of Engineering. Please contact tf-dekan@fau.de with any questions.

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).

A postdoctoral research position is available at Johns Hopkins University in the laboratory of Dr. Mounya Elhilali to investigate representation of complex sounds in both biological and artificial networks. The position is available immediately for two years, with possibility of renewal.

The ideal applicant will have a doctoral degree in computer science, electrical engineering, applied mathematics, neuroscience, psychology, hearing or brain sciences, with strong quantitative skills.

Johns Hopkins is an outstanding intellectual environment for medical and engineering research. The laboratory is affiliated with the department of Electrical and computer engineering as well as the Center for Speech & Language Processing and the Center for Hearing and Balance, and has strong research collaborations with the departments of Biomedical Engineering, Psychology and Brain Sciences, Computer Science, Mechanical Engineering as well as the schools of Medicine and Public Health.

Interested applicants should send a brief cover letter, a curriculum vitae with sample publications, and 2 reference contacts to mounya(at)jhu(dot)edu.

The speech technology research group at the IBM T. J. Watson Research Center in Yorktown Heights, NY is seeking research scientist candidates with demonstrated publication records in top machine learning, speech, vision, or natural language processing conferences. The role will focus on fundamental research on speech recognition models and algorithms, in collaboration with other IBM researchers and the IBM Data and AI development organization, as well as delivery of new technologies into IBM's Watson speech services.

Required Professional and Technical Expertise:
• Expert in programming, experimental, and quantitative skills
• Intermediate experience in deep learning
• Proven publication track record at top machine learning, speech, vision, or natural language processing conferences
• Strong communication and collaboration skills

Preferred Professional and Technical Expertise :
• Proficiency with PyTorch or other deep learning frameworks
• Prior experience in speech recognition is welcome but not necessary

Required Education : Doctorate Degree

To apply: https://krb-sjobs.brassring.com/TGnewUI/Search/home/HomeWithPreLoad?partnerid=26059&siteid=5016&PageType=JobDetails&jobid=387939