We are seeking for a highly motivated and innovative Scientist with a strong expertise in molecular dynamics of protein complexes, and biological simulations :
“Computational Chemist in Protein Molecular Dynamics – 18 months Temporary Contract“
Within the Research Informatics department, He/she will be responsible for:
- Exploring innovative modes of action of proteins, including allostery, with molecular dynamics (MD) techniques.
- Developing and validating prediction algorithms for the identification of candidate areas in proteins for non-orthostheric modulation, like cryptic pockets, protein-protein interaction sites.
He/she will have the following missions:
- Provide structure-based support to projects and realize key contributions to milestones.
- Explore, create, and develop methods for the identification of protein pockets, segments, and domains, for non-orthostheric modulation.
- Perform research on original computational modeling and simulation methods for innovative therapeutic biomolecular modulation.
- Incorporate Machine Learning approaches in the computational workflow.
- Collaborate with computational chemists, bioinformaticians, biologists, structural biologists, and omics scientists in collaborative project teams.
- Keep up-to-date with relevant professional literature and share methods and techniques with computational chemistry and project colleagues.
- Present work results at project meetings, and group and department meetings.
- Write and contribute to publications and patents where possible.
- Participate to the scientific life of the Computational Chemistry Group, and Evotec
Knowledge, skills and abilities :
- Expertise in molecular dynamics of protein complexes, and biological simulations.
- Experience of methods and techniques used in molecular biosimulations : e.g. enhanced MD, accelerated MD, steered MD, umbrella sampling, replica exchange, normal modes, multiscale modeling, Monte Carlo simulation, structural clustering
- Excellent knowledge of at least one MD package: Amber, Gromacs, NAMD
- Knowledge of protein structures, protein dynamics, protein-protein and protein-ligand interactions and simulation. Good knowledge of signal membrane proteins.
- Explicit simulation of membrane proteins
- Experience in developing and implementing molecular modeling algorithms to study protein complexes.
- Knowledge of machine learning approaches for data mining.
- Scripting experience, e.g. Python
- Scientific rigor and excellent analytical and synthetic capabilities.
- Ability to establish, to maintain effective working relationships, and to work collaboratively.
- Strong communication skills.
- Dynamic person with passion for innovation.
- Written and spoken English
Experience and education :
- PhD in a relevant scientific discipline : Computational Chemistry, Computational Biophysics, Structural Biology or equivalent
- Minimum of 2 years post-doctoral academic or industrial experience in related activity
- Publications in molecular dynamics of protein complexes and innovative methods to decipher protein dynamics and interactions.