Research Assistant

Research Assistant Would you like to work with machine learning, supported by competent and friendly colleagues in an international environment? Do you want an employer that invests in sustainable employee engagement and offers secure, advantageous working conditions? Welcome to apply for the position of research assistant at Uppsala University. The Department of Cell and Molecular Biology is divided into seven research programs focusing on various areas within cell and molecular biology: computational biology and bioinformatics, microbiology, molecular biology, molecular biophysics, molecular evolution, molecular systems biology, and structural biology. The scientific foundation of our work lies within biology, but our research overlaps with other fields such as medicine, computer science, mathematics, chemistry, engineering, and physics. The department has over 200 employees, including approximately 60 doctoral students. Please read more about the organization’s work at https://icm.uu.se. Job Responsibilities The successful candidate will work on a project aimed at clarifying how mutations affect protein stability, with a particular focus on disease-associated mutations. The work involves method development at the intersection of machine learning and physics-based computational methods. Responsibilities include: scientific programming in Python, particularly further development of the internal code QresFEP (https://github.com/qusers/qligfep); identification, collection, and curation of mutation data for evaluation and testing of the method; large-scale molecular dynamics simulations and free energy calculations; as well as analysis of simulations, including the development of deep learning models to interpret and complement the free energy calculations. Qualifications The applicant should have a bachelor's degree in chemistry and a master's degree in pharmaceutical development or equivalent. Experience with molecular simulation techniques such as molecular dynamics and free energy calculations should be documented with publications in the research field. The applicant should have a background in (e.g., through specialized courses or teaching experience) structural and/or pharmaceutical bioinformatics, thermodynamics, statistical mechanics, and deep learning. Experience in a scientific computing environment, including Unix-based systems, use of high-performance computing resources, bash/shell scripting, and scientific programming in Python is required. The applicant must have excellent communication skills in English, both spoken and written, and be able to work independently as well as collaborate effectively. Desirable/Additional Qualifications Teaching experience, particularly focused on supervising students' independent projects or research preparatory components, as well as experience with deep learning methods in biochemical or biophysical applications, is considered an asset. About the Position The position is temporary, lasting 3.5 months. The scope is full-time. Start date is January 1, 2026, or as agreed. Location: Uppsala. For inquiries about the position, please contact: Professor Johan Åqvist (+46 18 471 41 09, [email protected]). We welcome your application no later than December 8, 2025, UFV-PA 2025/3622. Uppsala University is a broad research university with a strong international standing. Our ultimate goal is to conduct education and research of the highest quality and relevance to make a difference in society. Our most important asset is our 7,600 employees and 53,000 students who, with curiosity and commitment, make Uppsala University one of the most exciting workplaces in the country. Read more about our benefits and what it’s like to work at Uppsala University at https://uu.se/om-uu/jobba-hos-oss/. The position may be subject to security clearance. A prerequisite for employment is that the applicant is approved during the security assessment. We kindly decline offers of recruitment and advertising assistance. Applications are received through Uppsala University’s recruitment system. Union representatives: Saco-S - [email protected], Seko - [email protected], ST (OFR/S) - [email protected].