You will join our R&D team in to develop the algorithmic solution for the core process unit currently supported in DataHowLab. This involves building and refining innovative hybrid models that combine mechanistic understanding with data-driven approaches – a cutting-edge methodology that sets DataHow apart in the industry.
You will design, implement, and validate upstream bioprocess models, translating scientific knowledge into robust, well-structured code. Ideally, you bring strong capabilities in machine learning and data science combined with programming skills.
Key Responsibilities
- Tackle real-world problems, working with several datasets across multiple domains for our customers and partners.
- Assist in the development and implementation of novel machine learning models and algorithms for multivariate timeseries prediction.
- Develop, deploy, benchmark and maintain new and existing sections of the modeling code base.
- Stay current with the latest advancements in machine learning, finding innovative ways to apply cutting-edge methods and other effective techniques to our challenges.
- Collaborate closely with fellow R&D engineers, data scientists, product and project teams to integrate models into DataHowLab.
- A strong university degree (minimum MSc or equivalent) in Computer Science, Data Science, Statistics, Mathematics, or a related field
- Strong understanding of machine learning concepts and algorithms.
- Proficiency in programming languages used for Data Science such as Python or Julia.
- Experience with machine learning libraries and frameworks (PyTorch, scikit-learn, JAX)
- Familiarity with data manipulation and analysis packages and tools (e.g., Pandas, Polars, NumPy, SQL).
- Experience in solving differential equations with numerical methods.
- Excellent problem-solving skills and attention to detail.
- Ability to work effectively in a team environment.
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.