PhD Project in Statistical Machine Learning

Updated: about 1 month ago

DTU Compute’s Section for Cognitive Systems would like to invite applications for a 3-year PhD position starting 1st April 2020 or as soon as possible thereafter. The project is financed by DFF, the Independent Research Fund Denmark, through the project "Few-shot generative models”.

The Section for Cognitive Systems is a lively and research oriented group of scientists and support staff with a shared interest in information processing in man and computer, and a particular focus on the signals they exchange - audio, imagery, behavior – and the opportunities these signals offer for modeling and engineering of cognitive systems. The Section is working actively to keep a healthy work-life balance and we are aware of the challenges facing young families in academia. Working at DTU provides much flexibility and families in Denmark enjoy a highly developed and affordable childcare system.

Project Description
Modern flexible statistical models such as those used in deep learning are very data hungry. They require a lot of training data to perform well. A strong theme in contemporary deep learning research is therefore the development of methodology that can give high predictive performance even for small datasets. This can be achieved through transfer, multitask, meta- and few-shot learning. These methods use information from other similar tasks or other prior knowledge. In this project we build upon research expertise in Cognitive Systems to make new hierarchical generative models for unsupervised few-shot and meta-learning. These new models can be applied in contexts where one wants to solve multiple tasks that share some characteristics. Although the main focus is unsupervised learning extensions to supervised and model based reinforcement learning are also of interest.

Responsibilities and tasks
Are you interested in developing new statistical machine learning methods based on probabilistic modeling, deep learning, and computer science? Then you might be our new PhD student. You will be involved in all tasks of the project. In particular you will:  

  • Develop and implement hierarchical generative models for few-shot and meta-learning. 
  • Contribute to documenting and disseminating the research results in scientific journals and top conferences like NeurIPS, ICLR and ICML. 
  • Develop, document, and publish open source software to make the research available to the community. 
  • Be part of and contribute to a research group focused ambitious research in contemporary machine learning.

Through the project will gain a deep understanding of probabilistic modelling and modern computational research using GPU accelerated computing. We expect that you are motivated and self-driven, and strive for excellence.

Candidates should have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree. The master degree should be in computational science and engineering (CSE), applied mathematics, or engineering, or equivalent academic qualifications.

Preference will be given to candidates who can document experience in statistical machine learning and experience with working in PyTorch or similar frameworks. Furthermore, good command of the English language is essential.

Approval and Enrolment
The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in the DTU Compute PhD School Programme. For information about the general requirements for enrolment and the general planning of the PhD study programme, please see the DTU PhD Guide .

The assessment of the applicants will be made by Professor Ole Winther.

We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

Salary and appointment terms
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The position is a full-time position. The period of employment is 3 years starting 1st April 2020 (or as soon as possible thereafter).

You can read more about
career paths at DTU here .

Further Information
Further information concerning the project can be obtained from Ole Winther, [email protected] .

Further information concerning the application is available at the DTU Compute
PhD homepage .

Please submit your online application no later than 21 February 2020 (23:59 local time)Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply online", fill out the online application form, and attach all your materials in English in one PDF file. The file must include: 
  • A letter motivating the application (cover letter)
  • Curriculum vitae
  • Grade transcripts and BSc/MSc diploma
  • Excel sheet with translation of grades to the Danish grading system (see guidelines and Excel spreadsheet here )

Candidates may apply prior to obtaining their master's degree, but cannot begin before having received it.

Applications and enclosures received after the deadline will not be considered.

All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply.

DTU Compute is an internationally unique academic environment spanning the science disciplines mathematics, statistics and computer science. At the same time we are an engineering department covering informatics and communication technologies (ICT) in their broadest sense. Finally, we play a major role in addressing the societal challenges of the digital society where ICT is a part of every industry, service, and human endeavour.

DTU Compute has a total staff of 400 including 100 faculty members and 130 Ph.D. students. We offer introductory courses to all engineering programmes at DTU and specialised courses to the mathematics, computer science, and other programmes. We offer continuing education courses and scientific advice within our research disciplines, and provide a portfolio of innovation activities for students and employees.

Technology for people
DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN’s 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear vision to develop and create value using science and engineering to benefit society. That vision lives on today. DTU has 11,500 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. Our main campus is in Kgs. Lyngby north of Copenhagen and we have campuses in Roskilde and Ballerup and in Sisimiut in Greenland.

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