Postdoc - Deep Learning and Perturbation Models

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 is a dynamic and innovative institution engaged in the development of artificial intelligence (AI) methods for biomedical applications. In this highly explosive and relevant field of research we are one of the largest and most recognized centers in Germany. On a national and international level we are active and recognized in numerous initiatives and networks.

The Institute of Computational Biology is globally recognised for innovations in data analysis and modelling of biological systems and diseases, anchored at Helmholtz Munich and the Technical University of Munich. At our institute you will find a scientifically stimulating international environment.

The Theis Lab has a long-standing reputation for pioneering machine learning and AI methods in molecular biology, in particular on single-cell genomics.

We are seeking a highly motivated and talented Postdoctoral Researcher (f/m/x) to join our team for a collaborative research project with Pfizer Inc. The project aims to enable target discovery and precision medicine through the application of scalable and interpretable deep learning and perturbation models. As a Postdoctoral Researcher, you will play a key role in developing and implementing innovative machine learning algorithms and computational methods to accelerate target discovery, inform precision medicine, and enable preclinical to clinical translation.
 

Your tasks

• Curate, prepare, and analyze immune cell CRISPR data.
• Integrate large-scale clinical omics data and metadata from public and private clinical studies.
• Develop Deep Learning algorithms to compare human diseases and preclinical models.
• Model both genetic and chemical perturbations in out-of-distribution conditions.
• Mentor highly-motivated PhD students.

Your profile

• Ph.D. in Computer Science, Bioinformatics, Computational Biology, or a related field with a focus on machine learning, deep learning, or artificial intelligence.
• Strong background and research experience in developing, applying, and evaluating deep learning algorithms.
• Proficiency in programming languages such as Python and experience with deep learning frameworks (e.g., TensorFlow, PyTorch).
• Experience in analysing and integrating large-scale omics data (e.g., RNA-seq, bulk transcriptomics, single-cell data) and applying machine learning methods.
• Familiarity with perturbation models, genetic perturbations, and compound data is a plus.
• Good publication record and excellent communication skills.
• Ability to work collaboratively in a multidisciplinary team

If you fulfil all the requirements, you may be eligible for a salary grade of up to E 13. Social benefits are based on the Collective Wage Agreement for Public-Sector Employees (TVöD). The position has an (initial) fixed term of 2 years but may be extended under certain circumstances.

We are committed to promoting a culture of diversity and welcome applications from talented people regardless of gender, cultural background, nationality, ethnicity, sexual identity, physical abilities, religion or age. Qualified applicants with physical disabilities will be given preference.
If you have obtained a university degree abroad, we will require further documents from you regarding the comparability of your degree. Please request the Statement of Comparability for Foreign Higher Education Qualifications as early as possible.


Interested in applying?

If you have any questions, feel free to contact Marco Uhrig, marco.uhrig@helmholtz-munich.de, or Emma van Holthe, emma.vanholthe@helmholtz-munich.de, who will be happy to help.

Your application should include

• CV
• Cover letter
• Contact details for at least two referees

Application deadline: 31.05.2024