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Helmholtz Zentrum München 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, launches Helmholtz AI: This dedicated, interdisciplinary platform will compile, develop, foster and promote applied artificial intelligence (AI) methods nationwide for all Helmholtz centers in collaboration with its external and university partners. Its central unit is currently being implemented in Munich, one of Germany's major hubs for applied AI, at the Helmholtz Center Munich.

Postdoc for Deep Federated Learning with Medical Imaging (f/m/x) 100829

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Image Neuherberg near Munich
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Your mission

    Albarqouni lab's research focuses on developing innovative deep Federated Learning algorithms that can distill and share the knowledge among AI agents in a robust and privacy-preserved fashion. Research topics include, but not limited to, 
    i) handling distributed DL models with data heterogeneity including non i.i.d, and domain shifts, 
    ii) developing explainability and quality control tools for distributed models, and 
    iii) robustness to data and models poisoning attacks. 

    In this context, we are looking for a Postdoc who has a strong background in Machine/Deep Learning to push our understanding of robustness in Federated Learning algorithms. The candidate will be also contributing to interdisciplinary projects with other Helmholtz centers working with multidisciplinary team members.

  • Developing state-of-the-art (SOTA) federated learning algorithms in robustness to data and model poisoning attacks, and benchmarking to existing SOTA algorithms.
  • Contribute to interdisciplinary projects with other Helmholtz Centers and clinical partners.
  • Define and supervise master thesis projects.

Your qualifications

  • PhD in Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning with a track record of publications at top-tier conferences and high-impact journals in the field.
  • Strong knowledge in Machine/Deep Learning with experience in discriminative models, variational inference, and Bayesian neural networks.
  • Interest in solving challenges related to federated learning; data heterogeneity, system heterogeneity, robustness, and interpretability.
  • Excellent analytical, technical, and problem solving skills.
  • Excellent programming skills in Python and PyTorch.
  • Excellent communication and presentation skills, including experience in communicating across discipline boundaries.
  • Desired qualifications
  • Experience in supervision of students.
  • Hands-on experience with Federated Learning and MONAI framework.
  • Working in a Linux environment, with experience of shell scripting, cluster, or cloud computing.
  • Fluency in spoken and written German.

What we offer you

continuous education and training
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work-life balance
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flexible working hours & time off in lieu
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30 days annual leave
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on-site health management service
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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 world-leading research institutions it offers an intellectually stimulating environment.

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

To promote diversity, we welcome applications from talented people regardless of cultural background, nationality, ethnicity, gender and sexual identity, physical abilities, religion and age. Qualified applicants with physical disabilities will be given preference.

We are looking forward to receiving your comprehensive online application until 20 June 2021. Please send your application (in English) in a single PDF fileincluding:
a) Motivation letter: describe your long-term research vision, the reason for applying to be part of our lab, and why you think you are the right candidate to fill this position (max. 2 pages)
b) 
Curriculum vitae incl. list of publications 
c) copy of your diploma/degree certificates and
d) at least two reference letters (or the names of two referees).

Applicant guidance on the Corona pandemic

Interested?
If you have further questions, simply contact Shadi Albarqouni, shadi.albarqouni@helmholtz-muenchen.de.
Helmholtz Zentrum München
Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH)
Helmholtz AI
Ingolstädter Landstraße 1

85764 Neuherberg

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