PhD scholarship in Representation Learning

Do you want to advance state of the art in machine learning research by learning useful and operational representations? Common representation learning is useful for solving a given task, but in unsupervised learning the task is less clear and statistical identifiability problems start appearing. In this project you will advance the capabilities of unsupervised learning techniques for understanding proteins by building geometric machine learning models.

Responsibilities and qualifications
Most learned representations are treated as being Euclidean even if it is trivial to construct counter-examples showing that the Euclidean assumption lead to arbitrariness. You will join a team of people dedicated to avoiding this arbitrariness. You will work with nonlinear generative models and use geometric techniques to develop well-defined operations that can be meaningfully applied in the representation space of the model. The end-goal is to both improve the modelling capacity of generative models, but also to improve their general interpretability.

Depending on interest and qualifications of the applicant, the project can be either theoretical, applied, or a combination thereof. We generally believe that theory and applications must go hand in hand to ensure that the theory is meaningful and beneficial to scientific discovery.

You must 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.

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

Assessment
The assessment of the candidates will be made by Professor Søren Hauberg.

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 period of employment is 3 years. Starting date is as soon as possible according to mutual agreement.   

You can read more about career paths at DTU here.

Further information
Further information may be obtained from Søren Hauberg, sohau@dtu.dk / www2.compute.dtu.dk/~sohau/.  

You can read more about DTU Compute at compute.dtu.dk/english.  

If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark.   

Application procedure
Your complete online application must be submitted no later than 1 January 2022 (Danish 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)

You may apply prior to ob­tai­ning your master's degree but cannot begin before having received it.

Applications 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
DTU Compute is a unique and internationally recognized academic department with 385 employees and 11 research sections spanning the science disciplines mathematics, statistics, computer science, and engineering. We conduct research, teaching and innovation of high international standard – producing new knowledge and technology-based solutions to societal challenges. We have a long-term involvement in applied and interdisciplinary research, big data and data science, artificial intelligence (AI), internet of things (IoT), smart and secure societies, smart manufacturing, and life science. At DTU Compute we believe in a diverse workplace with a flexible work-life balance.

The Section for Cognitive Systems is an internationally renowned group for machine learning research. The group aims for the highest quality research. You're 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.

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 12,900 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. DTU has campuses in all parts of Denmark and in Greenland, and we collaborate with the best universities around the world.

Deadline: 2022-01-01 at 23:59
Unit: DTU Compute

Read the job description at the university homepage or Apply.

Post expires on lørdag januar 1st, 2022