PhD scholarship in Geometric Bayesian Deep Learning – DTU Compute

PhD position on the intersection of Bayesian deep learning and differential geometry.
In this project, we will develop a theoretical understanding of the failure modes of Bayesian deep learning and translate these insights into efficient and scalable approximate inference techniques. Do you want to figure out why Bayesian deep learning doesn't work? And afterwards fix it? At DTU Compute, we are working towards building highly scalable Bayesian approximations that actually work for deep learning. The driving approach is to first figure out the root cause of why the usual tricks do not work and then secondly fix the issues.

You will join a highly motivated and collaborative team under the supervision of Søren Hauberg. The research environment favors creative 'slow thinking' style research, and we emphasize having fun along the way. Our work is consistently published at the top venues of machine learning research.

Qualifications
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.

You should have prior experience with machine learning from both a theoretical and practical perspective. Experience in one of the following topics will be appreciated, but mostly we look for smart people who enjoy learning new things:

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

We tend to work in teams, so a collaborative spirit is required.

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 DTU's rules for the PhD education.

Assessment
The assessment of the applicants will be made by 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 with a negotiable starting date.

Further information
Further information may be obtained from Søren Hauberg at ,

Application procedure
Your complete online application must be submitted no later than 15 September 2024 23:59 (Danish time) . Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply now", 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 (in English) including official description of grading scale

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.

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.

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