Data Scientist – Process Modelling

Company Description

At Algocell, we use machine learning and mathematical modeling to improve how cells grow and produce things like proteins and materials. Our platform combines physics-based models with data-driven approaches to help biotech companies run better experiments with less guesswork. If you're excited by real-world challenges involving hybrid models, uncertainty, and optimization—this is a place to apply your skills beyond the usual ML stack.

Role Description

• Develop hybrid models that integrate biological insights with advanced machine learning techniques.
• Address stochastic differential equation (SDE) challenges by creating uncertainty estimation frameworks and conducting stochastic simulations to inform robust control strategies.
• Optimize process control policies using reinforcement learning methods (e.g., policy-gradient, model-free RL) to maximize yield and adapt to plant-model mismatches.
• Build reusable, production-grade code in Python and integrate models into our cloud-based platform.

Qualifications

• 3+ years of industry experience in data science or algorithm development roles.
• MSc or PhD in Computer Science, Electrical Engineering, Bioinformatics, Chemical/Biochemical Engineering, Data Science, or a related field from a top-tier university.
• Strong proficiency in Python programming.
• Excellent communication skills and a collaborative mindset.
• A proactive, startup-oriented attitude.

Nice-to-Haves

• Experience with hybrid models, Physics-Informed Neural Networks (PINNs), Neural ODEs, or scientific machine learning.
• Background in biology or experience with precision fermentation and cell-culture manufacturing.
• Familiarity with cloud deployment (AWS/GCP), Docker, and CI/CD best practices.

🚀 Ready to Join Us?

Apply now - send your CV to [email protected] or via LinkedIn. Let’s accelerate the bioprocess revolution together!