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Lund University

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PhD in Computational Chemistry and Machine Learning for Binding Affinity Prediction at Lund University Lund University in Sweden

Degree Level

PhD

Field of study

Computer Science

Funding

Fixed-term full-time doctoral employment at Lund University for 4 years, with possible extension for teaching and other departmental duties up to 20% of working hours. The post is a salaried doctoral studentship with monthly salary; no stipend amount is stated.

Deadline

Expired

Country flag

Country

Sweden

University

Lund University

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Keywords

Computer Science
Machine Learning
Chemistry
Biology
Mathematics
Computational Chemistry
Molecular Modeling
Quantum Mechanics
Pharmacy
Statistical Mechanics
Bioinformatic
Physics

About this position

PhD opportunity in Computational Chemistry at Lund University in Sweden, focused on machine learning, binding affinity prediction, and drug discovery. The project is based in the Division of Computational Chemistry and the Computational Biochemistry group, working with quantum chemistry, statistical mechanics, biochemistry, medicinal chemistry, and structural biology.

The doctoral project aims to develop physics-informed machine-learning models for predicting the binding affinity of small molecules to biological macromolecules. The work starts from physics-based approaches such as MM/PBSA, free-energy perturbation, SQM 2.20, and fragment molecular orbital calculations, then uses modern ML methods to improve predictions and identify the physical information most relevant to binding.

The project involves close collaboration with Molecular AI at AstraZeneca and the Department of Pharmaceutical Biosciences at Uppsala University. The post is a full-time fixed-term doctoral employment starting 2026-09-01 or as agreed. The employment is for 4 years, with possible extension for teaching and other departmental duties (up to 20%).

Eligibility includes a second-cycle qualification and a relevant background such as Computational Chemistry, Bioinformatics, Machine Learning, Computer Science, Mathematics, Statistics, Physics, or a related discipline. Required skills include Python programming, independent research ability, strong communication skills, good English, and a collaborative mindset. Preferred experience includes machine learning for scientific problems, molecular modelling, molecular mechanics/dynamics, quantum mechanics, binding affinity prediction, HPC, workflow automation, and collaborative software development.

Applications must be written in English and include a CV, cover letter, degree/study certificates proving eligibility, and any additional documents such as transcripts, references, or recommendation letters. Apply via the Varbi portal before the deadline.

Deadline: 2026-04-26

Funding details

Fixed-term full-time doctoral employment at Lund University for 4 years, with possible extension for teaching and other departmental duties up to 20% of working hours. The post is a salaried doctoral studentship with monthly salary; no stipend amount is stated.

What's required

Applicants must have a second-cycle qualification or equivalent, and for specific admission a Master of Science in Computational Chemistry, Bioinformatics, Machine Learning, Computer Science, Mathematics, Statistics, Physics, or a related discipline. Required skills include proficiency in programming such as Python, the ability to work independently and formulate research problems, strong written and oral communication skills, good spoken and written English, a collaborative mindset, and strong motivation. Preferred qualifications include experience with modern machine-learning methods, molecular modelling, molecular mechanics, molecular dynamics, quantum mechanics, small-molecule binding affinity prediction, computational workflow tools, high-performance computing, workflow automation, collaborative software development, and relevant courses in quantum mechanics, statistical mechanics, medicinal chemistry, and bioinformatics.

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Professors

Professor

University Name
Country flag

Sweden

Research Interests

Pharmacy

Quantum Mechanics

Computer Science

Chemistry

Biology