University of Tromsø

What you'll study

The master's programme in Computational Chemistry at the University of Tromsø combines theoretical foundations with hands-on computer modelling. The programme is delivered as a research-oriented two-year degree (master's level) and typically comprises advanced taught courses plus a substantial research thesis. Core topics include electronic structure theory (Hartree–Fock, post-Hartree–Fock and density functional theory), molecular dynamics and Monte Carlo simulation, statistical mechanics, potential energy surface construction, and methods for spectroscopy and reaction dynamics.

Typical taught modules and skills you will encounter:

• Quantum chemistry and electronic structure: wavefunction methods, DFT, basis sets and excited-state methods.
• Molecular dynamics and statistical mechanics: classical MD, ab initio MD, enhanced sampling and free-energy methods.
• Computational spectroscopy and reaction dynamics: calculation of IR, Raman and electronic spectra, transition state theory and kinetics.
• Method development and scientific programming: algorithm design, numerical methods, code development in Python, Fortran or C/C++ and use of established packages.
• Materials modelling and soft matter: modelling of solids, interfaces, clusters, and complex molecular assemblies.
• High-performance computing and data analysis: parallel computing, workflow management and reproducible research practices.

The programme culminates in an independent research project and thesis supervised by UiT academic staff. Projects frequently involve use of the university's high-performance computing resources and can be experimental–computational collaborations with other departments or external research partners, focusing on topics such as catalysis, atmospheric and cryospheric chemistry, energy materials or biomolecular simulations.

Entry requirements

Applicants should hold a relevant bachelor's degree or equivalent qualification in chemistry, physics, materials science, chemical engineering, or a closely related discipline, with a solid grounding in physical chemistry, mathematics and basic programming or computational courses. Specific course prerequisites typically include undergraduate quantum chemistry or physical chemistry and courses in calculus and linear algebra.

Admission is competitive and considers academic transcripts, letters of recommendation, a statement of purpose and, where relevant, prior research experience. International applicants must demonstrate English proficiency through recognised tests unless exempt. Where applicants lack some background, bridging courses or prerequisite coursework may be required before or during the programme.

Career prospects

Graduates with an MSc in Computational Chemistry are prepared for a wide range of careers. Common pathways include doctoral research and academic positions, industrial research and development in pharmaceuticals, materials, chemical and energy sectors, and roles in national laboratories and research institutes. Computational chemists also work in software development for scientific computing, data analysis and machine learning applied to chemical problems, and in consultancy roles addressing environmental and process modelling.

Employers value the combination of theory, practical modelling skills and HPC experience acquired at UiT; graduates often contribute to multidisciplinary teams working on energy materials, catalysis, Arctic environmental chemistry, sensors and drug design.

Why study at University of Tromsø

UiT The Arctic University of Norway offers a unique research environment for computational chemistry, combining strong theoretical groups with access to national and regional high-performance computing facilities. The university's location in the Arctic provides distinctive opportunities to study chemical processes relevant to cold climates, atmospheric chemistry and cryospheric systems, often in collaboration with institutes and industry partners.

Students benefit from close supervision, opportunities to join active research projects, and interdisciplinary collaborations across physics, chemistry, earth sciences and biotechnology. The department emphasises method development, reproducible workflows and transferable programming skills, preparing graduates for both academic and applied careers.