About the Role

You will join our R&D team to develop the algorithmic backbone for chromatographic process unit within 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 chromatographic models, translating scientific knowledge into robust, well-structured code. Ideally, you bring both strong programming skills and hands-on laboratory experience in chromatography, enabling you to bridge the gap between experimental science and computational modeling.

 

Key Responsibilities

  • Develop and implement mechanistic and hybrid models for chromatographic separation processes
  • Develop, deploy, benchmark and maintain new and existing sections of the modeling code base.
  • Stay current with the latest advancements in chromatographic or more generally partial differential equation modeling, leveraging 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
Requirements
  • A strong university degree (minimum MSc or equivalent) in Computer Science, Data Science, Statistics, Mathematics, or a related field
  • Solid understanding of chromatographic separation processes (ion exchange, affinity, hydrophobic interaction, etc.)
  • Proficiency in Julia and/or Python for scientific computing and model development
  • Experience with numerical methods, simulation, and/or parameter estimation
  • Experience in solving differential equations with numerical methods.
  • Excellent problem-solving skills and attention to detail.
  • Ability to work effectively in a team environment.
We Offer

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.

Transforming Digital
Bioprocessing