As a Process Modeling Engineer on our Customer Team, you will play a key role at the interface between cutting-edge process modeling and real-world industrial applications. The position combines technical depth with customer-facing responsibilities and offers the opportunity to work closely with our international clients and multidisciplinary internal teams. You will be required to:
Process Modeling & Data Analysis
- Conduct independent research and analysis using deterministic, statistical, and hybrid models for time-series and dynamic process data.
- Collaborate with industrial partners to translate complex process challenges into actionable model-based insights.
Modeling & Machine Learning Expertise
- Design, implement, and validate machine learning and statistical models tailored to bioprocess data, ensuring robustness, interpretability, and practical applicability.
- Integrate process engineering knowledge with data-driven approaches to build hybrid mechanistic-ML models.
- Work with numerical methods (e.g., ODE solvers, optimization routines) and experiment with advanced approaches such as dynamic modeling, Bayesian methods, or reinforcement learning where applicable.
- Ensure reproducibility and maintainability of modeling workflows through clean coding practices, documentation, and version control (GitLab).
Customer-Facing Activities
- Deliver process data analysis and modeling services to a diverse international client base through both DataHowLab and custom machine learning implementations.
- Participate in cross-functional teams—internally and on the client side—to support multidisciplinary decision-making.
- Communicate technical results and key insights clearly from scientific, operational, and business perspectives.
Training & Support
- Lead client training sessions on DataHowLab to ensure strong user adoption and effective usage.
- Provide ongoing technical support and guidance to clients.
Internal & Strategic Contributions
- Contribute to organizational, operational, and marketing initiatives that support the growth of our customer and user community.
- Examples include: visits to our Zurich headquarters, participation in our annual DataHow Symposium, and contributions to internal knowledge sharing or customer success processes.
- Excellent university degree (Master’s or PhD preferred) in computer science, (bio)informatics, (bio)statistics, chemical engineering, biotechnology, or related fields.
- Expertise in modeling of time-series or dynamic process data.
- Solid coding experience in Python.
- Experience in data analytics and machine learning.
- Strong communication skills and enthusiasm for interacting with clients in a scientific/technical context.
- Ability to work effectively in cross-functional teams as well as independently.
- Fluency in written and spoken English.
- Motivation to work in a fast-moving, internationally active start-up.
- Understanding of biopharmaceutical processes and unit operations (e.g., cell culture, chromatography, filtration, virus inactivation).
- Experience with numerical solutions of ODE/PDE systems or optimization problems.
- Familiarity with Python data science tools (NumPy, Pandas, PyTorch, scikit-learn, etc.).
- Experience using GitLab for project collaboration.
Integration into a young, dynamic, and interdisciplinary team of computationally driven chemical engineers, biotechnologists, and computer scientists. Hybrid work model, with flexibility between our main office in Lisbon and home office. A highly versatile role balancing advanced research, real-world industrial applications, and customer interaction. A steep learning curve, significant responsibility, and exposure to high-impact international projects. Opportunities for travel, conferences, and participation in company-wide community events. Attractive working conditions and clear opportunities for career progression.