PhD Project "Multi-modal Deep Neural Networks to understand the cis-regulatory code at single-cell resolution" (Sasse, 01)

Employer

Centre for Molecular Biology of the University of Heidelberg, Heidelberg University, Heidelberg, Germany

Description

The cis-regulatory code governs when, where, and how much of gene products are created in cells, enabling the formation of various cell types from a single genome. Variants disrupting this code can lead to genetic diseases. Experimentally measuring all cis-regulatory sequence variations is nearly impossible. However, deep sequence-to-function models can learn the relationship between genomic sequences and their regulatory function from massive collections of genome-wide datasets. In this process, they gain knowledge about the regulatory sequence grammar of our cells which can be used to predict the effects of unseen regulatory sequences. However, current state-of-the-art models have limitations, particularly in understanding complex sequence grammar arising from the complex multi-layered regulatory processes or the interplay of distal sequence elements. Improving these models' foundational understanding of gene regulation involves enhancing cell type resolution, integrating various data modalities, and using cross-species data. This poses significant engineering challenges, and new model architectures are needed to effectively manage and learn from the large, and diverse datasets. This project will develop multi-modal sequence-to-function models and new explainable AI methods in pytorch or similar deep learning environments to understand the cis-regulatory code of multi-cellular species.

Candidate requirements

We are looking for a highly motivated PhD candidate holding a Master's in computer science, computational biology, bioinformatics, or similar. A strong background in computational biology, Machine Learning with pytorch or similar deep learning libraries is required.

About the employer

Our junior research group is part of the newly founded CZS Center SynGen (https://www.syn-gen.de/) and the Center for Molecular Biology (Zentrum für Molekulare Biologie Heidelberg, ZMBH, https://www.zmbh.uni-heidelberg.de/) at the renowned Heidelberg University. The CZS Center SynGen is supported by the Carl-Zeiss-Stiftung to promote research and development at the participating Universities in Heidelberg, Karlsruhe and Mainz to develop an internationally visible research focus on Synthetic Genomics. The ZMBH has a long tradition of conducting cutting-edge research in molecular and cell biology, as well as biomedicine. With the CZS Center SynGen Initiative the ZMBH is on a mission to contribute to the developments in synthetic genomics with fundamental, theoretical or applied research towards programmable biology.

Further details

Our Junior research group develops Deep Genomic Sequence-to-Function (S2F) models to explore how genomic sequences influence gene regulatory functions (More about projects). These highly scalable models integrate various data modalities that measure different aspects of gene regulation in a high-throughput manner. Our research is at the forefront of advancing these models' foundational understanding of gene regulation. We are pursuing three exciting directions: 1) Scaling up current models with single-cell data across diverse species and data types, 2) Incorporating readily available cell type-specific data to train the next generation of cell type-agnostic models, capable of predicting for unseen cell types and conditions, and 3) Developing new generative models to leverage S2F’s foundational knowledge for creating synthetic regulatory elements with tailored properties for biotechnology.

Possible start of employment: Friday, 01 November 2024.

Contract: Full-time, Fixed-term

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