Machine Learning Scientist – Nucleic Acid Sequence Design

You develop and apply machine learning models to design DNA and RNA sequences for nucleic acid-based medicines, working closely with wet-lab teams.

Your tasks

• Build, train and fine-tune machine learning algorithms for nucleic acid-based medicines
• Design sequence libraries for lab-in-the-loop optimization cycles
• Analyze experimental readouts such as MPRA and NGS and iteratively update designs
• Collaborate with wet-lab scientists and project leads on therapeutic design constraints
• Present technical findings and model performance to cross-functional stakeholders
• Contribute to scientific publications

What you bring

• Ph.D. in a quantitative discipline such as bioinformatics, computational biology or machine learning
• 0-4 years of post-doctoral or industry experience
• Research impact at the interface of machine learning and molecular biology, evidenced by publications
• Strong Python programming skills and proficiency in deep learning frameworks such as PyTorch
• Hands-on experience developing or fine-tuning sequence-to-function models for biological molecules
• Excellent communication skills in English with computational and experimental scientists

Conditions

• Workload: 100 %
• Option of a permanent position after the assignment if both sides want it

Technologies

• Python
• PyTorch

How to apply

You apply with your Try&Hire profile: upload your CV, check the details, enter key facts and availability. A short introduction video is optional but helps. Our team will get in touch if your profile fits the assignment.