Machine Learning Data Scientist

About the Role:

• You will develop hybrid mechanistic/ML cell response models that predict fermentation outcomes from process and sensor data.
• You will fuse time-series signals from process analytical technology with offline analytics and build mechanistic backbones.
• You will drive research from scoping to delivery, owning hard, open-ended problems with autonomy.

How You'll Work:

• Collaborate with technical leads and external partners to design and execute research that meets consortium commitments.
• Work closely with wet lab, dry lab, and software teams, and identify data needs from the robotic lab.
• Communicate clearly with non-ML partners and present your work with leading European academic and industrial groups.

Key Research Areas:

• Hybrid bioprocess modelling, transfer learning across organisms and scales, and real-time model-predictive control.
• Build the AI/ML layer for nonlinear model predictive control and reinforcement-learning-based feeding strategies.
• Use frontier coding models and modern ML tooling such as PyTorch/JAX and scikit-learn.

Benefits and Culture:

• Competitive compensation through salary and stock options.
• Opportunity to build your research profile and publish work.
• Beautiful office in Munich or remote work option with occasional travel, plus eGym WellPass membership.