Postdoc in Geometric Machine Learning

DTU Compute
onsdag 07 feb 18

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Frist 15. marts 2018
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DTU Compute’s Section for Cognitive Systems, invite applications for an appointment as Postdoc within geometric machine learning. The position is available from April, 2018 or according to mutual agreement.

Our department 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 strives to achieve research excellence in its basic science disciplines, to achieve technological leadership in research and innovation, and to address societal challenges in collaboration with partners at DTU and other academic institutions, nationally and internationally, and, equally important, with industry and organizations. We communicate and collaborate with leading centres and strategic partners in order to increase participation in major consortia.

DTU Compute plays a central role in education at all levels of the engineering programmes at DTU - both in terms of our scientific disciplines and our didactic innovation.

The aim of the new position is to expand the Departments research in geometric machine learning and probabilistic numerics.

The project focus on learning locally adaptive metrics and building statistical models that respect these. We model the locally adaptive metric as a Riemannian metric, which gives a firm mathematical foundation to build upon. We are interested in building both theoretical foundations and practical algorithms working with this class of models. Working on this, you will develop new insights using differential geometry, machine learning, probability theory, and much more. The focus of the project will depend on the chosen candidate. Potential topics of research include (but are not limited to): 

  • (Smooth) metric learning
  • Latent variable models
  • Probabilistic numerics
  • Statistics on Riemannian manifolds

More details are available at www2.compute.dtu.dk/~sohau/positions/.  

Responsibilities and tasks
The main task of the position is to conduct independent research at the highest international level. You will be part of a dedicated team aiming to build and understand geometric models in machine learning. You will be a senior member of this team, so you are expected to contribute to the overall research direction of the team. Depending on interests, a small teaching load, mostly in the form of student supervision, can be part of the position.

Qualifications
Candidates should have a PhD degree or equivalent.

Curiosity, motivation, and an easy going personality. Those are the key characteristics that we look for in a candidate. The projects we work on take inspiration from many diverse communities, so you will most likely only be familiar with some aspects of the projects before you start.

The ideal candidate will have experience with:

  • probabilistic models, ideally in a machine learning context;
  • geometric models, ideally with a focus on differential and Riemannian geometry;
  • numerical implementations of mathematical models on Matlab/Octave and/or python.

We do not expect that the chosen applicant will be an expert in all these topics, but do expect the will and ability to learn such diverse topics.

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 an academic freedom tempered by responsibility.

Salary and terms of employment
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed with the relevant union. The period of employment is 2 years. The applicant is expected to work from the DTU Campus in Lyngby, Denmark.

You can read more about career paths at DTU here.  

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

You can read more about the Department on www.compute.dtu.dk.   

Application procedure
Please submit your online application no later than 15 March 2018 (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 in the online application form, and attach all your materials in English in one PDF file. The file must include: 

  • Application (cover letter)
  • CV
  • Diploma (MSc/PhD)
  • List of publications
Applications and enclosures received after the deadline will not be considered.

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

DTU Compute has a total staff of 400 including 100 faculty members and 130 Ph.D. students. We offer introductory courses in mathematics, statistics, and computer science 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.

DTU is a technical university providing internationally leading research, education, innovation and scientific advice. Our staff of 5,800 advance science and technology to create innovative solutions that meet the demands of society; and our 11,000 students are being educated to address the technological challenges of the future. DTU is an independent academic university collaborating globally with business, industry, government, and public agencies.