Machine Learning for Signal Processing

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.

The Department of Computer Science at the National University of Singapore is seeking a postdoctoral fellow to work with Dr. Jonathan Scarlett.

The postdoctoral fellow will work on problems at the intersection of machine learning, statistical signal processing, information theory, and their intersection, with topics potentially including the following:
- Algorithms and theory for high-dimensional inference and learning (e.g., graph learning, structured estimation)
- Sequential decision-making algorithms under uncertainty (e.g., black-box optimization, bandits, ranking)
- Information-theoretic limits for problems in statistical inference, learning, and optimization
- Machine learning methods applied to communication problems
Further information on Jonathan Scarlett's research interests can be found at https://www.comp.nus.edu.sg/~scarlett/.

The position is expected to last for at least 1 to 2 years. The candidate should have a PhD in a relevant area such as machine learning, statistical signal processing,  information theory, or theoretical computer science, and a strong publication record. 

The salary will be very competitive, and commensurate with the candidate's abilities and track record. 

Applicants should submit a detailed CV and a short statement of research interests to Jonathan at scarlett@comp.nus.edu.sg. Shortlisted applicants will later be asked to arrange for at least two reference letters to be sent to the same address

I have an open position in my group for a fully funded PhD student. The requirements are strong background in Mathematics and Signal Processing. Familiarity with Machine Learning and Communication Theory are preferable.

Please email me your: 1) transcripts, 2) updated CV, and 3) GRE and TOEFL (if applicable) scores to elnaz.banansadeghian@wichita.edu. Please include in your CV the contact information of your references who can write recommendation letters for you.

The Department of Computer Science at the National University of Singapore is seeking a postdoctoral research fellow to work with Dr. Jonathan Scarlett.

The postdoctoral fellow will work on problems at the intersection of information theory, statistical signal processing, and machine learning, with topics potentially including the following:
- Algorithms and theory for high-dimensional inference and learning (e.g., graph learning, structured estimation)
- Sequential decision-making algorithms under uncertainty (e.g., black-box optimization, bandits, ranking)
- Information-theoretic limits for problems in statistical inference, learning, and optimization
- Machine learning methods applied to communication and signal processing problems
Further information on Jonathan Scarlett's research interests can be found at https://www.comp.nus.edu.sg/~scarlett/.

The position is expected to last for at least 1 to 2 years. The candidate should have a PhD in a relevant area such as information theory, statistical signal processing, machine learning, or theoretical computer science, and a strong publication record. 

The salary will be very competitive, and commensurate with the candidate's abilities and track record. 

Applicants should submit a detailed CV and a short statement of research interests to Jonathan at scarlett@comp.nus.edu.sg. Shortlisted applicants will later be asked to arrange for at least two reference letters to be sent to the same address.

 

The Institution for Future is a newly established department in Qingdao University, nestling under the mountain and beside the sea in the beautiful coastal city of Qingdao. We have millions of funding and now seeking for some teammates who wish to lead the future with us. The following five labs are opening for candidates at all ranks (Post-Docs, assistant, associate, and full professor):

• Lab of Artificial Intelligence
• Lab of Robotics
• Lab of Intelligent Manufacture
• Lab of Unmanned Systems
• Lab of Fundamental Research

We are interested in candidates in broad areas, including but not limited to: control theory and technology, computer science, signal processing, robotics, unmanned systems, artificial intelligence. You will be given large freedom for your own research and/or industrial projects.

The assistant professor position and Post-Doc position is only for young scientists under 35. The Post-Doc position lasts about 2 years (usually no less than 20 months, no more than 3 years). Special offers are available for outstanding candidates now.

To apply or to request more information, please contact jwy1992@126.com as soon as possible. Application documents should include a detailed CV, publication record, your best 2 papers, and preferably a proposal for your future research.

About the position:

We have a vacancy for a PhD Research Fellow position at the Department of Electronic Systems (IES). The PhD position is for up to 4 years with 25% work assignments for NTNU IES.

Job description:

The pervasion of the Internet of Things (IoT), which connects numerous sensors, actuators, appliances, vehicles etc., has a strong impact on the evolution of smarter and greener cities as well as on environmental monitoring. A basic tenet underlying all key functionalities of the IoT is situational awareness, i.e., the ability to capture events and derive accurate critical information for decision making that enable timely action in a heterogeneous and highly dynamic environment. This calls for an intelligent infrastructure that is autonomous, dependable, and resilient to natural or man-made disturbances. A critical component of such an infrastructure comprises myriads of information-gathering sensors deployed at many points of concern in the city. The sensors deployed in smart cities' IoT constitute critical data sources, on which the ensuing analytics and control actions depend. Those sensors are interconnected through the internet, forming an important part of IoT, and most likely powered only by batteries. To ensure that the sensors function effectively, we need to take a holistic approach to designing secure sensor networks with energy-efficient functional algorithms starting with sensing, followed by data processing and communication to ensure reliable decision making to enable timely actions that make possible long lasting secure and dependable functionality.

The PhD projects will be around developing and analyzing new efficient statistical learning algorithms for distributed inference to improve data quality, reliability, privacy and security of the physical-layer signals in IoT. The aim is to go beyond state-of-the-art solutions, embrace a secureby-design philosophy by exploiting additional information available at the physical layer, and take a holistic approach that starts with smart sensors, smart inference, and secure two-way communication among all the devices in the network, and energy-efficiency.

We seek a highly-motivated individual who has

• strong mathematical background and a research-oriented master thesis in a related field, e.g., signal processing, information theory, statistical machine learning, applied mathematics, or optimization
• experience with programming

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

Qualification requirements:

The qualification requirement is completion of a master’s degree or second degree (equivalent to 120 credits) with a strong academic background in Electrical Engineering, Applied Mathematics, Computer Science, or other relevant disciplines with a grade of B or better in terms of NTNU’s grading scale. Applicants with no letter grades from previous studies must have an equally good academic foundation. Applicants who are unable to meet these criteria may be considered only if they can document that they are particularly suitable candidates for education leading to a PhD degree.

Application:

For more detailed information and application submission, please visit the following link:

https://www.jobbnorge.no/en/available-jobs/job/158760/phd-position-in-signal-processing-for-privacy-preserving-distributed-learning-in-iot

The submission should contain an application letter describing your motivation, relevant experience, skills and qualifications, and a brief research vision for the position (maximum 2 pages) along with a CV, publication list, MSc thesis, letters of reference, proof of fluency in the English language (if applicable) and grade transcripts from both bachelor and master’s degrees.

Title: Speech research/machine learning internship @Alibaba

Time: Fall2018, Spring2019

Job location: Seattle, WA /  San Francisco, CA / Beijing

Link: https://sites.google.com/site/gangliuresearch/jobs

About You

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

About Us:

We are Machine Intelligence Technology -Intelligent Speech Interaction-Speech, Alibaba Group (U.S.) Inc. We enable hundreds of millions of commercial and social interactions among our users, between consumers and merchants, and among businesses every day though speech. We are on the top a gold mine of high quality big data with millions of real data samples.

What You’ll Do

Develop and refine algorithms to improve speech system performance under adverse conditions. To be specific, we will assign either of the following project to you according to your background:

1) Speaker recognition: feature & model design, system fusion

2) Emotion Identification: data purification, prediction with limited out-of-domain data, feature & model design

At the end of internship, a conference paper is expected.

Skills You’ll Need

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

Proficiency in audio signal processing and robust acoustic feature engineering is a plus

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

Deep learning (DNN, CNN, LSTM)

Familiarity with C++, Python, Bash shell

Familiarity with Kaldi, DNN toolkits

Solid publication record

Contacts:

Gang Liu

gDOTliu@alibaba-incDOTcom

please use . to replace DOT

（Application is processed on a rolling basis）

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 in September/October 2018 (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 candiidates should contact Prof Sergei Turitsyn [s.k.turitsyn@aston.ac.uk]  in the first instance.

PHD PROGRAM in TRANSLATIONAL NEUROSCIENCES AND NEUROTECHNOLOGIES

The Center for Translational Neurophysiology of Speech and Communication (CTNSC) @ Italian Institute of Technology (IIT), is looking for highly motivated students to work on:

- Improving performance and biocompatibility of electrode arrays for brain-computer interfaces - Functional investigation of innovative neural interfaces - Investigation of sensorimotor functions in animal models (NH primates and rats) - Machine learning applications to multimodal brain and speech signals - Human neurophysiology of speech and sensorimotor communication - Cortical recordings in human patients during awake Neurosurgery - Hardware and software development for innovative exploration of brain signals   We are looking for computer scientists, biomedical/electrical engineers, biologists or experimental psychologists eager to work in an international and multidisciplinary team.

Where: The CTNSC is hosted by the University of Ferrara (UNIFE) in a prestigious historical building in the city center. UNIFE is one of the oldest Universities (founded in 1391) and in terms of its size, facilities, quality, and quantity of education and research is a point of excellence within Italy.

Ferrara is a well connected (30-min to Bologna, 40-min to Padua, 60-min to Venice), lively and affordable student city (https://whc.unesco.org/en/list/733).

Application INFO: http://www.unife.it/studenti/dottorato/concorsi/selection

DEADLINE: 23 July 2018

Title:  Speech research/machine learning internship @Alibaba

Time: Summer/Fall, 2018

Job location: Seattle /  San Francisco / Beijing

Link:  https://sites.google.com/site/gangliuresearch/jobs

About You

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

About Us:

We are Machine Intelligence Technology -Intelligent Speech Interaction-Speech, Alibaba Group (U.S.) Inc.  We enable hundreds of millions of commercial and social interactions among our users, between consumers and merchants, and among businesses every day though speech.  We are on the top a gold mine of high quality big data with millions of real data samples.

What You’ll Do

Develop and refine algorithms to improve speech system performance under adverse conditions. To be specific, we will assign either of the following project to you according to your background:

1) Speaker recognition: feature engineering, modeling, deep learning, system fusion 

2) Acoustic Event Identification:  data purification, audio event classification, abnormal audio event detection 

At the end of internship, a conference paper is expected.

Skills You’ll Need

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

Proficiency in audio signal processsing and robust acoustic feature engineering is a plus

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

Speaker/Language/Accent Identification is a plus

Speaker Recognition Anti-spoofing is a plus

Deep learning (DNN, CNN, LSTM)

Familiarity with C++, Python, Bash shell

Familiarity with ASR, DNN toolkits

Solid publication record

Contacts:

Gang Liu

gDOTliu@alibaba-incDOTcom

please use . to replace DOT