Postdoctoral Researcher, Machine Learning & Cheminformatics

Would you like to explore how quantum computing could accelerate innovation in the bioeconomy? Do you want to work at the interface of academia and industry and contribute to turning science into impact? VTT might be just the place for you. 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 a Postdoctoral Researcher, Machine Learning & Cheminformatics, to join our Rise to Challenge project Q-GEN: Quantum computing applications for future genomes and biomaterials. In this two-year postdoctoral position, you will develop a data-driven screening workflow for biomaterial design. The workflow will combine molecular representations, machine learning, physics-based supercomputer simulations, and experimental data to predict how chemical modifications influence and structure the properties of wood-based biopolymers. The resulting methods will be used as classical baselines for comparison with emerging approaches in quantum computing. You will work as part of an interdisciplinary team of experts from chemistry, mathematics and physics, collaborating closely with a dedicated group of quantum physicists who will design and run the quantum algorithms. Our Bioinspired materials team develops novel biomass-based materials and applications and seeks new ways to valorise wood-based materials beyond the traditional pulp and paper industry. In the Q-GEN project, we work with partner organisations that include experts from genomics, synthetic biology, foresight and ethics, and focus specifically on developing new materials for the bioeconomy. “This is a genuinely new way of developing biomaterials. Instead of using computational simulations to explain what has already been observed in the laboratory, we are now using them to explore and identify promising material combinations before experiments begin. Bringing machine learning, physics-based simulation and quantum computing into the development of forest biomaterials opens up an exciting new research landscape.” — Mikko Mäkelä, Research Professor As a Postdoctoral Researcher, you will: Develop machine learning methodologies to predict biopolymer properties from molecular representations, physics-based simulations, and experiments. Interpret results together with chemists and physicists and help experimental researchers by identifying promising candidates for wet-lab experiments. Establish and validate classical baselines for comparison with quantum computing. Collaborate with experts in quantum computing, genomics, synthetic biology, foresight and ethics across partner organisations. Communicate results through scientific publications, project reporting and presentations. Contribute to new project ideas and future research proposals in chemical and material informatics. Who we are looking for: You have a doctoral degree in a relevant field, such as computer science, data science, machine learning, chemical or material informatics, or a closely related discipline. Your doctoral degree was completed no more than five years ago. You have strong practical experience in data-driven modelling and at least one of the following: molecular representations, quantitative structure-activity relationships, or chemical or material informatics. You can work with molecular representations and connect molecular structure to measured or simulated material properties. You have strong programming skills in Python or a comparable scientific programming language, and can develop documented and reproducible computational workflows. Experience with cheminformatics tools, such as RDkit, is considered an advantage. You have a strong scientific track record relevant to the position and the ability to produce high-quality scientific outputs. You communicate fluently in English and are comfortable working in an international, multidisciplinary research environment. As a person, we hope that you are: Curious and eager to learn, with an open mindset towards new scientific fields and methods. A collaborative team player who can build common understanding with people from different disciplines and perspectives. Proactive and accountable: you take ownership of moving work forward, deliver on your commitments and communicate openly when plans need to change. Motivated to build networks and develop new research ideas together with colleagues and external partne