Sought-After Researcher in Geometric Bayesian Deep Learning

1 day ago


Kongens Lyngby, Lyngby-Tårbæk Kommune, Denmark Danmarks Tekniske Universitet (DTU) Full time

Company Overview

Danmarks Tekniske Universitet (DTU) is a leading technical university globally recognized for the excellence of its research, education, innovation, and scientific advice.

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.

Job Description

We are seeking a highly motivated researcher to join our team in the field of geometric Bayesian deep learning. In this project, you will develop a theoretical understanding of the failure modes of Bayesian deep learning and translate these insights into efficient and scalable approximate inference techniques.

Required Skills and Qualifications

To be successful in this role, you must have a two-year master's degree or a similar degree with an academic level equivalent to a two-year master's degree. You should also have prior experience with machine learning from both a theoretical and practical perspective.

Experience in one of the following topics will be appreciated:

  • Approximate Bayesian inference
  • Differential geometry
  • Numerical computations (ideally with experience in Jax)
  • Large-scale computations

Benefits

As a researcher at DTU Compute, you will have the opportunity to work in a highly collaborative and international environment. Our research environment favors creative 'slow thinking' style research, and we emphasize having fun along the way.

Others

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.



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