Doctoral Student in Computational Chemistry

Prof. Dr. Sereina Riniker's group for Computational Chemistry at the Institute of Molecular Physical Science is interested in the development of methodology for classical molecular dynamics simulations and cheminformatics, and in the application to address challenging biological and chemical questions.

The Doctoral Network MC4DD"MC4DD – Macrocycles for Drug Discovery", funded within the framework of the Marie Sklodowska-Curie Actions (MSCA), follows an interdisciplinary and cross-sectoral approach by bringing together leading experts in macrocyclic drug discovery from academia and industry from the fields of organic synthesis, medicinal, high-throughput and computational chemistry, pharmacological and structural analytics, and modelling.

Eight academic research groups and five industrial partners, coordinated by Technische Universität Darmstadt in Germany, join forces in MC4DD to create a mobility and training platform for young scientists by means of cross-site, interdisciplinary research projects. The DCs will work on individual research projects to expand the opportunities of macrocycles as next-generation drug modalities.

More information can be found here.

Objectives: 

• Characterization of the structure-permeability relationship of macrocycles using molecular dynamics simulations and comparison with NMR data 
• Development of novel conformation- and environment-dependent 3D descriptors based on the MD simulations
• Development and refinement of machine learning models for permeability prediction for macrocycles

Secondments planned within the framework of the Doctoral Network:

• Roche, Switzerland, C. Kroll: Experimental determination of PAMPA permeability coefficients for macrocyclic library
• U. Uppsala, Sweden, M. Erdelyi: Conformational studies by NMR experiments
• Bayer, Germany, D. Barber: Conformational sampling of macrocycles

Preferred starting date: early 2025.

Applicants should hold a M.Sc. in chemistry, computational chemistry, or physics. Experiences with machine learning and/or biomolecular simulation, and strong programming skills (Python) are highly advantageous. Proficiency in English, good communication skills, and social competence are required.

We welcome self-motivated candidates with outstanding academic record, excellent communication skills and professional integrity to apply. 

EU Mobility Rule: Researchers must not have resided or carried out their main activity (work, studies, etc.) in the country of the recruiting beneficiary >12 months in the 36 months preceding their recruitment date.

The project offers research and training excellence in medicinal chemistry and drug discovery. The partners of MC4DDare leading research groups in this field and their research institutes actively promote young researchers. The 8 academicresearch groups and 5industry partners join forces in MC4DD to create a platform of intersectoral andmultidisciplinary mobility and training.

To complement the academic and scientific goals of the doctoral students, the project offers customized research projects, structured interdisciplinary local and network-wide transferable skills training activities, and secondments at top-rankingEuropean universities and industrypartners.