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PhD Project in Deep Generative Models and Missing Data

Danmarks Tekniske Universitet (DTU)



Frist 12. august 2020

DTU Compute’s Sections for Cognitive Systems, would like to invite applications for a 3-year PhD position starting November 1, 2020 (or as soon as possible). The project is financed by a grant from the Independent Research Fund Denmark, and the PhD student will be supervised by Associate Professor Jes Frellsen.

The Section for Cognitive Systems is an internationally renowned group for machine learning research. The group aims for the highest quality research. You are encouraged to collaborate both within the group and with other international groups. We emphasize a healthy work/life balance based on the premise that you do the best work when you are happy.

Project Description
Incomplete data are ubiquitous in all branches of science and technology. Data with values missing-not-at-random (MNAR) is the most complex type of incomplete data, and ignoring the missing process when learning from this kind of data can lead to biased estimates of model parameters. The objective of this project is to study and develop methods for learning deep generative models that jointly learn the data generating process and missing-data mechanism in MNAR data. We will consider models based on Variational Autoencoders (VAEs), normalizing flows and Generative Adversarial Networks (GANs). Of particular interest is advanced inference techniques, heterogeneous data and how to make minimal but principal modelling assumptions about the missing process, but the focus will depend on the chosen candidate. We are interested in various applications within image analysis, collaborative filtering and bioinformatics.

The project includes collaborations and stays with Professor Julie Josse at École Polytechnique and Research Scientist Pierre-Alexandre Mattei at INRIA in Sophia Antipolis.

Responsibilities and tasks
As a PhD student, your responsibilities include:

  • Carrying out research for your PhD project
  • Writing and publishing scientific papers
  • Attending PhD courses
  • Teaching and dissemination of your research
  • A stay (abroad) at an external research institution

As a PhD student in the Section for Cognitive Systems, you will be part of a large, vibrant group of PhD students. There are several reading groups on contemporary topics in machine learning and various social activities. Furthermore, you will be part of an ample research environment working on deep generative models.

Qualifications
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’s degree should be in computational science and engineering (CSE), computer science, statistics, pure/applied mathematics, physics, or engineering, or equivalent academic qualifications.

Preference will be given to candidates who are excited about basic research, have an interest in the mathematical foundations of machine learning and have experience with mathematical modelling and the programming and tools needed to apply these models to real data. 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.

Assessment
The assessment of the applicants will be made by Associate Professor Jes Frellsen.

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 November 1, 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 Associate Professor Jes Frellsen.

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

Application
Please submit your online application no later than 12 August 2020 (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 (incl. list of publications or other research experience)
  • Grade transcripts and BSc/MSc diploma
  • Excel sheet with translation of grades to the Danish grading system (see guidelines and Excel spreadsheet here)
  • An example technical text you have written in English such as a report prepared for a course, a consulting project, or a published peer-reviewed scientific article.

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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Danmarks Tekniske Universitet (DTU)
Danmarks Tekniske Universitet (DTU)
DTU er et teknisk eliteuniversitet med international rækkevidde og standard. Vores mission er at udvikle og nyttiggøre naturvidenskab og teknisk videnskab til gavn for samfundet. 11.200 studerende uddanner sig her til fremtiden, og 6.000 medarbejdere har hver dag fokus på uddannelse, forskning, myndighedsrådgivning og innovation, som bidrager til øget vækst og velfærd.

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