The Center for Molecular Biology (ZMBH) at Heidelberg University is seeking a highly motivated PhD candidate or postdoctoral fellow to explore deep learning models and the evolution of mammalian gene regulation. The position is an exciting opportunity to work in a collaborative and internationally recognized environment focused on synthetic genomics.

The project focuses on understanding the evolution of cis-regulatory elements in mammals through the development of novel deep learning models. The successful candidate will integrate computational biology with machine learning techniques to explore gene regulatory functions.

Qualification

1.  A Master’s or PhD degree in computer science, computational biology, bioinformatics, or similar fields.
2.  Strong background in computational biology and machine learning, particularly with PyTorch or similar deep learning frameworks.