Postdoctoral Researcher in Computational Genomics : The research group of Oliver Stegle at EMBL Heidelberg is seeking a Postdoctoral Researcher to contribute to a collaborative project focused on applying machine learning and causal inference to decipher genetic networks from high-throughput perturbation data. The successful candidate will work within an interdisciplinary team to develop tailored methodologies for analyzing population-scale cohorts and perturbation screens, with a focus on gene regulation dynamics.
Postdoctoral Researcher in Computational Genomics – Causal Machine Learning for Gene Regulation
Designation: Postdoctoral Researcher
Research Area: Causal Machine Learning for Gene Regulation
Location: EMBL Heidelberg, Germany
Eligibility/Qualification: Candidates should hold a Ph.D. or equivalent qualification in computer science, statistics, mathematics, physics, engineering, or biological science with demonstrated experience in computational and statistical development. Strong programming skills in Python and experience with machine learning or statistical learning frameworks are required.
Job Description:
- Develop machine learning and causal inference methodologies for deciphering genetic networks from high-throughput perturbation data
- Collaborate with experimentalists and other computational scientists to analyze population-scale cohorts and perturbation screens
- Develop robust software solutions for data analysis and scale them to clinical applications
- Present results at conferences, contribute to publications, and participate in research proposal preparation
- Supervise and guide Research Assistants and Students
How to Apply: Interested applicants should submit their applications online through the EMBL website, including a cover letter and CV.
Last Date for Apply: 12 May 2024
