- Use molecular modelling to design and understand formulated drug products and delivery systems. This will cover solid amorphous systems, complex solid dispersions, formulated peptides with diverse functional excipients.
- Define ambitious research project plans, working with the team for focus realization, progressing execution of simulations, monitoring, and communicating towards goals.
- Develop proof-of-concept models and workflows to transform realization of novel peptide formulations.
- Explore new modelling approaches to address the complex interplay between pharmaceutical ingredients in a formulated product and publish your novel science.
- Work collaboratively with colleagues in other functions and contribute to the optimization of experimental work to complement in silico models.
- Tackle sophisticated scientific problems and provide lean and innovative solutions.
- PhD level education in Computational Chemistry, Physics, Solid State Biology, Biophysics, or a relevant subject area.
- Experience of applying molecular modelling to drug like molecules, proteins or other similar organic molecules.
- An excellent understanding of principles of physical chemistry related to solid state of amorphous systems.
- Knowledge of scripting languages such as Perl, Python or BASH. Experience working in Unix/Linux environments and High-performance computing (HPC). Strong oral and written communication skills and the ability to discuss complex ideas in a simple, easy to understand way.
- A proven track record of working collaboratively in a team environment to deliver project objectives.
- Actively seeks out innovative approaches and new scientific advances in the field, using internal and external networks.
- Knowledge of protein molecule dynamics, and processing of protein solution into solid state for generating amorphous protein formulation.
- Knowledge of bio-chemical and bio-physical degradations in amorphous glass materials, especially on the role of excipients in local stabilization involving beta relaxation including formulation matrix dynamics.
- Good chemistry, thermodynamic and solid-state knowledge to improve end-to-end software applied to complex solid state systems using e.g. programs such as Gromacs, VASP, CP2K, Materials Studio, CCDC suite, Schrödinger package or equivalent is beneficial. Good knowledge of Python programming, and scripting.
- Experience or knowledge in, at least, one of these extra methods: free energy calculation, QM/MM, enhanced sampling methods or force field development.