Postdoc in modelling and digital twin development Full-time NEW

Postdoc In Modelling And Digital Twin Development

Would you like to build a physics-based model and a digital twin of how bio-based materials are pressed and dried? We are looking for a postdoc at the Department of Fibre and Polymer Technology at KTH and the Wallenberg Wood Science Center.

In a Formas-funded project together with Hitachi Energy and Nordic Seafarm, we develop knowledge and tools to reduce the energy used in the dewatering and drying of bio-based materials. Your role is to develop a robust numerical model of mechanical dewatering and subsequent thermal drying and to advance it into a validated digital twin of the process.

You will work within a continuum porous-media framework – Darcy flow coupled to heat transfer with phase change – and implement the model in existing codes and/or COMSOL, including AI-tools. You will calibrate and validate the model against experimental data, demonstrate a digital twin using industrial or lab data, and work closely with an experimental postdoc and industrial partners.

Qualifications

Requirements

• A doctoral degree or an equivalent foreign degree. This eligibility requirement must be met no later than the time the employment decision is made.
• Documented scientific expertise in numerical modelling and simulation of coupled physical phenomena, demonstrated through publications.
• Experience of finite element or finite volume methods and scientific programming, e.g. Python, MATLAB, C++ or Fortran.
• Very good command of English, spoken and written, as it is required in the daily work.
• As a person you are independent, take initiative and have a strong ability to collaborate in an interdisciplinary environment.

Preferred qualifications

• A doctoral degree or an equivalent foreign degree, obtained within the last three years prior to the application deadline
• Experience of COMSOL Multiphysics or equivalent multiphysics simulation software.
• Experience of modelling dewatering, drying or wet pressing of pulp, paper or fibre networks.
• Experience of calibrating and validating models against experimental data, or of digital twins and reduced-order models.
• Teaching abilities.
• Awareness of diversity and equal opportunity issues, with specific focus on gender equality.

Great emphasis will be placed on personal skills.