Postdoc AI in regulatory genomics

19.03.2024, Wissenschaftliches Personal

Passionate about AI in regulatory genomics? The lab of Julien Gagneur at the Technical University of Munich (TUM) is seeking a talented and driven individual to join our dynamic team. As part of the newly funded ERC Synergy consortium EPIC, you will develop new modeling strategies for regulatory genomics.

About us

The Chair of Computational Molecular Medicine, led by Prof Julien Gagneur, develops computational approaches to study the genetic basis of gene regulation and its implication in diseases. Applications of our work range from understanding basic mechanisms governing gene expression to unraveling genetic aberrations triggering rare diseases and cancer. More at https://www.cs.cit.tum.de/cmm/home/.

The project

EPIC is a 10-million Euro project funded for 6 years by the European Research Council under the ERC Synergy grant scheme. EPIC brings together 3 groups at the edge of complementary technologies – Vicente Pelechano (Karolinska Institute) for the development of high-throughput omics assays, Kevin Verstrepen (VIB-KU Leuven) for synthetic biology, and Julien Gagneur for the AI and bioinformatics. EPIC aims at deciphering the complete regulatory code, from chromatin to protein abundance, of the eukaryote S. cerevisiae. To this end, EPIC takes a unique attack angle leveraging evolution. We will assay 100 fungal species spanning over hundreds of millions of years across all layers of gene regulation and under different growth conditions. Moreover, EPIC will design nearly a million sequences to systematically test and refine our model of the regulatory code and eventually design genes and cells for biotechnological applications. Our research group will develop new AI modeling paradigms to learn from such multi-modal and multi-species data effectively. This will allow us to unravel complex regulatory instructions and their evolution, build predictive models, and design genes with intended regulation.

Your role

You will contribute to the conception and development of new algorithms spanning:
large language modeling of DNA and RNA sequences
self-supervised and semi-supervised modeling strategies
Multi-modal modeling, spanning all levels of gene regulation from chromatin accessibility to protein abundance via transcript boundary choice, RNA stability, and localization.
algorithms for MPRA and gene design
You will interact with other postdocs. You will mentor and be supported by more junior colleagues (PhD candidates, Bachelor’s and Master’s students).

Requirements

PhD degree in Computational biology or related (Computer Science, Physics)
Experience with NGS data processing and modeling
Experience with the conception, implementation and training of deep learning models
Excellent organizational skills and good mentoring capabilities
Fluent in English. Communicate clearly in a multidisciplinary collaborative setting

We offer

The position can start on July,1st 2024. It is funded until June, 31st 2030
Salary according to the TV-L (German academic salary scale) - E13. It includes social benefits (healthcare, pension, and unemployment insurance)
International, attractive, and interdisciplinary working environment. The TUM CS department, among the top-ranked in Europe, gives access to excellent colleagues and students
Flexible working hours and home-officing policy
Disabled applicants with equal suitability and qualification will be given particular consideration
The TUM is striving to increase the proportion of women and hence applications from women are therefore expressly welcomed

Application
Applications should include a cover letter, CV, transcripts, and references and must be sent to [email protected] by Sunday, April 14th 2024 referring to “EPIC - Postdoc 2” in the email title. We process and store your application files in accordance to the Art. 13 General Data Protection Regulation (GDPR) for the collection and processing of personal data https://portal.mytum.de/kompass/datenschutz/Bewerbung/ (scroll down for the English version). By submitting your application, you confirm that you have read TUM's data protection information.

More Information
https://www.cs.cit.tum.de/cmm/home/
https://tum.de

The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance.

Data Protection Information:
When you apply for a position with the Technical University of Munich (TUM), you are submitting personal information. With regard to personal information, please take note of the Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. (data protection information on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm that you have acknowledged the above data protection information of TUM.

Kontakt: [email protected]