Master's Thesis Position in Computational Biophysical Chemistry of Biomaterials and Food

VTT is one of the leading applied research organisations in Europe. What unites us are curiosity, a passion for learning, and a purpose: to solve the biggest challenges of our time and turn them into sustainable growth and well-being. Our cross-disciplinary community of over 2000 brilliant minds from 55+ different nationalities focuses on creating impact through science-based innovation. In recent years, we have created ground-breaking innovations such as the world's fastest and most accurate radiation detector, a cancer-sniffing sensor device for smartphones, and a headphone set entirely made of microbial materials. Get to know us further by exploring VTT's tech & infra . We are now looking for Thesis Worker to join our Bioanalytics and biological Data Science team. We are seeking a highly motivated Master's student interested in the biophysical chemistry of food and biomaterials. We offer several potential thesis topics, and the project can be tailored to match the candidate's scientific interests, background, and career goals. Potential Thesis Topics 1. Molecular Modelling of Protein-Based Biomaterials Protein-based materials offer unique opportunities for creating sustainable biomaterials with tunable properties. However, their broader industrial adoption is still limited by challenges related to performance, predictability, and production costs. Our research focuses on developing multiscale computational models of protein-based materials, ranging from atomistic descriptions of intrinsically disordered proteins to coarse-grained simulations and machine learning approaches for materials design. The ultimate goal is to establish predictive frameworks that connect molecular properties to material performance. For more information, see: Nature Communications Chemistry article Research Leader Programme profile 2. Molecular Interactions in Food Systems Food materials consist of complex mixtures of proteins, lipids, and polysaccharides. As the food industry transitions towards more sustainable and plant-based ingredients, a fundamental understanding of the molecular interactions governing texture, stability, taste, and functionality becomes increasingly important. We develop multiscale modelling approaches, from atomistic simulations of biomolecules to coarse-grained and machine learning models, to investigate the physical principles underlying food structure and behaviour. The generated knowledge supports the rational design of next-generation food products. For more information, see: NSF Food Innovation and Diversification to Advance the Bioeconomy 3. From Biomolecular Phase Separation to Products Phase separation and aggregation of biomolecules play a central role in the processing and functionality of both food materials and biomaterials. The microstructure formed during processing strongly influences the properties of the final product. Our objective is to understand how molecular-level interactions drive phase separation and self-assembly, and how these mechanisms can be leveraged to predict and control product properties. The work combines concepts from soft matter physics, statistical thermodynamics, molecular simulations, and data-driven modelling. For more information, see: NSF Food Innovation and Diversification to Advance the Bioeconomy Why this is a great Thesis opportunity? A thesis project at the interface of computational science, biophysics, food science, and artificial intelligence. Opportunity to contribute to internationally visible research in sustainable food and biomaterials. Access to state-of-the-art computational tools, high-performance computing resources, and extensive mentoring. A flexible project scope that can be adapted to the candidate's interests and expertise. Unique career opportunities at the interface of academia and industry Who we are looking for: Advanced Master's studies in biophysics, physical chemistry, biochemistry, physics, chemistry, or a related field. Programming skills in Python Interest in modern AI-assisted and agentic programming approaches for scientific research. Scientific curiosity and enthusiasm for solving complex interdisciplinary problems. Ability to work both independently and as part of a collaborative research team It's an advantage if your have experience from some of the following; machine learning or AI method development, using AI agents and AI-assisted software development tools, molecular modelling, computational chemistry, bioinformatics, or related computational methods. With VTT, you’ll enjoy: Natural sciences with an impact. VTT works on the cutting-edge of natural sciences, and we've invested in building state-of-the-art research facilities for natural sciences, such as the Bioruukki pilot infrastructure for bio- and circular economy. Our research agenda is dedicated to solving systemic and technological challenges, such as reaching carbon neutrality and unleashing the power of synthetic biology. That means that at VTT, your experti