Postdoc (f/m/x) in "Swarm Learning for precision medicine in infectious diseases and pandemic preparedness"

Postdoc (f/m/x) in "Swarm Learning for precision medicine in infectious diseases and pandemic preparedness"

102301
Full time
Neuherberg near Munich
Home Office Options

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 Computational Health Center (CHC) is globally recognized for innovations in data analysis and modeling of biological systems and diseases, anchored at Helmholtz Munich and the Technical University Munich. The Theis Lab has a long-standing reputation for pioneering machine learning and AI methods in molecular biology, in particular on single-cell genomics and microscopy. The position is co-supervised by Joachim Schultze (DZNE, Bonn) and includes lab visits in Bonn.
Prof. Matthias Tschöp (Dr. Med., Dr. hc.),

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

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 tasks

The role involves developing and applying decentralised machine learning/AI tools to analyse high-parameter flow cytometry and high-resolution single-cell multi-omics data for diagnostic purposes in a clinical multi-center study based on the ScanPy platform and Swarm Learning. The position is part of a national consortium including experts in the fields of data and information sciences, immunology, virology, clinical infectious diseases, and ethics.

It provides an opportunity for close collaboration with the Schultze Lab at the Department of Systems Medicine at the German Center for Neurodegenerative Diseases, along with the possibility of conducting longer research visits to Bonn. This innovative work sets a precedent for applying AI across medical disciplines. If you are enthusiastic about addressing critical questions in the field of AI in medicine and contributing to the progress of precision medicine, you are encouraged to apply for this postdoctoral position.

• Develop standardised and automated analysis systems, integrating AI applications for various biomedical data, such as single-cell genomics.
• Aid in implementing Swarm Learning technology across a network of university hospitals and research centres.
• Develop a disease severity classifier for COVID-19 based on high-parameter cytometry data.
• Conduct and assess both local and distributed analyses of single-cell multi-omics data produced within a clinical multi-center study spanning a network of German university hospitals.
• Develop an outreach strategy to raise awareness of the opportunities and risks of decentralised AI applications in medicine in Europe.
• Provide guidance and supervision of students.

Your profile

• PhD in computational biology, bioinformatics, computer science, or a related field.
• Excellent skills in the fields of artificial intelligence, machine learning and computational biology.
• Strong programming skills combined with a mathematical mindset.
• Evidence of the ability to conduct high-quality research and produce publications in top-tier journals.
• Experienced in addressing clinical and biomedical questions.
• Familiarity with statistical and machine learning methods for data analysis.
• A track record of publishing research in peer-reviewed journals.
• Excellent analytical, technical, and problem-solving skills.
• Highly motivated team player with excellent communication and presentation skills, including experience in communicating across discipline boundaries.

Benefits