Helmholtz Munich is a research center with the mission to discover personalized medical solutions for the prevention and therapy of environmentally triggered diseases and promote a healthier society in a rapidly changing world.

Germany’s largest research organization, the Helmholtz Association, launched Helmholtz AI: This dedicated, interdisciplinary platform develops and promotes applied Artificial Intelligence (AI) methods for all Helmholtz centers in collaboration with its external and university partners. Its central unit is implemented at the Helmholtz Munich.

Vincent Fortuin’s lab at Helmholtz AI focuses on the interface between Bayesian inference and deep learning with the goals of improving robustness, data efficiency, and uncertainty estimation in these modern machine learning approaches. Important research questions include, but are not limited to:

PhD candidate - Bayesian deep learning for science (f/m/x) 101844

Image Full time
Image Neuherberg near Munich
Image Professionals, PhD

Your responsibilities

In this context, the Fortuin lab is looking for a PhD candidate who has experience in Bayesian machine learning, deep learning, or similar, and who has a strong interest in the aforementioned research directions.

You will be working closely with the rest of the Fortuin lab to drive your own research and be involved in interdisciplinary projects within Helmholtz and additional international collaborations. You will be given ample opportunity to publish your scientific results and present them at international conferences.

Your qualifications

  • M.Sc. in computer science, statistics, or associated disciplines, with strong interest in Bayesian machine learning methods
  • Strong mathematical background in probability theory, statistics, or similar
  • Programming skills in Python (or equivalent), with good working knowledge of deep learning libraries, such as PyTorch or Tensorflow
  • Excellent analytical, technical, and problem-solving skills
  • Be highly motivated and a team player with excellent communication and presentation skills, including experience in communicating across discipline boundaries

Beneficial qualifications:

  • Track record of contributions to peer-reviewed publications and international conferences
  • Hands-on experience with Bayesian deep learning
  • Experience with shell scripting, cluster and/or cloud computing

What we offer you

scientific training at MUDS Graduate School
work life balance
flexible working hours
30 days annual leave
onsite health management service
Image career consultation
Image home office options
Image campus daycare & 5 weeks vacation childcare
Image company pension scheme
Image discounted public transport ticket

Munich, with its numerous lakes and its vicinity to the Alps, is considered to be one of the cities with the best quality of life worldwide. With its first-class universities and research institutes, it offers a scientifically inspiring environment.

Your scientific career is important to us, that’s why this position provides the opportunity for you to build specialist knowledge and gather significant professional experience.

Remuneration and social benefits are based on the collective wage agreement for public-sector employees at federal level (EG 13 75% TV EntgO Bund). The position is (initially) limited to three years, but under certain circumstances an extension can be arranged.

To promote diversity, we welcome applications from talented people regardless of gender, cultural background, nationality, ethnicity, sexual identity, physical abilities, religion and age. Qualified applicants with physical disabilities will be given preference. If you have obtained a university degree abroad, we require further documents from you regarding the recognition of the degree. Please request the recognition as early as possible.

We are operating on a rolling interviewing schedule, so there is no fixed deadline. We are looking forward to receiving your application, including:

If you have further questions, simply contact Vincent Fortuin, +49 89 3187-14531, who will be happy to be of assistance.
Helmholtz Zentrum München
Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH)
Helmholtz AI
Ingolstädter Landstraße 1

85764 Oberschleißheim

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