Postdoc/Research Assistant in Machine Learning for Health (f/m/x) Helmholtz Zentrum München Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH)
Anzeige vom: 25.01.2025

Postdoc/Research Assistant in Machine Learning for Health (f/m/x)

Standort:
  • München
Helmholtz Zentrum München Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH)

Zusammenfassung

  • Arbeitszeit
    Vollzeit
  • Typ
    Festanstellung
  • Qualifikationslevel
    B Ausübungsformen

Gewünschte Fähigkeiten & Kenntnisse

Machine Learning
Programmiererfahrung
High-Performance-Computing
Bioengineering
CAN
AWS
Python
Make
E-Health
Innovation
TensorFlow
Bash
Entwicklungsumgebungen
Exchange Traded Commodities
Linux
Support
MS Excel
Cloud Computing
Management
Organisation

Stellenbeschreibung

We are Helmholtz Munich. In a rapidly changing world, we discover breakthrough solutions for better health.

Our research is focused within the areas of metabolic health/diabetes, environmental health, molecular targets and therapies, cell programming and repair, bioengineering, and computational health. We particularly excel in the fields of basic research, bioengineering, artificial intelligence, and technological development.

Through this research, we build the foundations for medical innovation. Together with our partners, we seek to accelerate the transfer of our research, so that laboratory ideas can reach society and improve people's quality of life at the fastest rate possible.

This is what drives us. Why not join us and make a difference?

The Institute of AI for Health (AIH) at Helmholtz Munich is a European hub pioneering applied Artificial Intelligence (AI) and Machine Learning (ML) solutions for healthcare and clinical data analytics.

We are seeking postdoctoral researchers (f/m/x) in Machine Learning for Health to develop innovative AI methods addressing global health challenges, with a focus on translating these advancements into practical healthcare applications. Prof. Matthias Tschöp (Dr. Med., Dr. hc.), CEO of Helmholtz Munich:

"We believe that excellent research requires a range of different perspectives. Diverse teams reach better solutions and are more innovative in their research topics.



Ihre Aufgaben


Establishing our Diversity Management Strategy demonstrates our commitment to ensuring an appreciative company culture based on mutual respect. We are also implementing diversity-sensitive processes throughout our whole organization."

Your opportunity

In this role, you will create scalable AI solutions to analyze multimodal medical data, advancing patient stratification, disease progression prediction, and precision medicine for Tuberculosis.

Leveraging advanced models such as attention-based frameworks, transformers, and generative approaches, you will work with clinical trial data, electronic health records, and genomic biobanks.

Collaborative projects with leading global research consortia, industry, and international institutions will enable you to drive impactful research in global health.

Funded by Unite4Tb, a European initiative for innovative Tuberculosis treatments, this position offers a unique opportunity to apply your expertise and contribute to groundbreaking healthcare innovation on a global scale.



Ihr Profil


  • Ph.D. and/or postdoctoral experience with a strong background in machine learning, bioinformatics, computational biology, or a closely related field.

  • Demonstrated expertise in developing and applying machine learning models (sklearn, etc) and deep learning frameworks (PyTorch, TensorFlow, etc.) for analysing biomedical data.

  • Strong programming skills in Python are essential, with experience in processing large-scale datasets in a Linux/Bash environment.

  • Experience with High Performance Computing (HPC) or cloud computing services (AWS, GCP).

  • Proven track record of addressing clinical and biomedical research questions, with a strong focus on translational outcomes.

  • Experience with large language models for analysing biomedical images and multi-omics data, and deep learning algorithms aimed at precision medicine.

  • Knowledge in disease dynamics inference from clinical, epidemiological, and electronic health records data, and interest in fair AI practices for biomedical applications.

  • A publication record in high-quality venues that demonstrates meaningful contributions to the field.

  • Ability to work flexibly and collaboratively with a multidisciplinary team, including clinicians, epidemiologists, and representatives from health systems, particularly in developing settings within the area of Global Health.

  • Excellent communication, organisation, leadership, and decision-making skills.



Wir bieten Ihnen


  • Career Development: Postdoc program, scientific training & career center with tailored offers

  • Scientific Resources: State-of-the-art infrastruture and Core Facilities

  • Recreation: 30 days annual leave, flexi days, plus public holidays

  • International Staff Service: Support with the relocation and integration process in Germany

  • Health Promotion: Sports, company doctor, mental health initiatives

Profil

Fachliche Voraussetzung

  • Algorithmus, Amazon Web Services, Bash Shell, Bioinformatik, Cloud Computing, Computational Biology, Computerprogrammierung, Deep Learning, Diversitätsmanagement, Electronic Medical Records, Epidemiologie, Gesundheitssystem, Globale Gesundheit, High Performance Computing, Klinische Arbeiten, Klinische Forschung, Large Language Models, Linux, Lungentuberkulose (Fachkompetenz), Machine Learning, Medizinische Forschung, Medizinische Versorgung, Medizintechnik, Multidisziplinärer Ansatz, Personalisierte Medizin, Postdoc, Python, Pytorch, Tensorflow, Transformer

Persönliche Fähigkeiten

  • Entscheidungsfähigkeit, Führungskompetenz, Kommunikation, Soziale Kompetenz, Teamarbeit

Schulabschluss

  • Dissertation

Bewerbung

    Branche:

    Pharmazie / Chemie

    Arbeitgeber:

    Helmholtz Zentrum München Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH)

    Adresse:

    Helmholtz Zentrum München Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH)
    Ingolstadter Landstr 1
    85764 Oberschleißheim

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