The Filizola Lab (http://www.filizolalab.org) at the Icahn School of Medicine
 at Mount Sinai, located in New York City, USA, is inviting applications for 
a research scientist/postdoctoral associate position in the broad field of 
computational chemistry/biophysics/AI-driven drug discovery. The laboratory 
is best known for providing rigorous mechanistic insights into the structure,
 dynamics, and function of prominent drug targets, such as G protein-coupled 
receptors (GPCRs), transporters, channels, transcription factors, and beta3 
integrins, with the ultimate goal of accelerating drug discovery. To this 
end, we employ several computational structural biology, cheminformatics, and
 artificial intelligence (AI)-based approaches, including molecular dynamics 
simulations, enhanced sampling methods such as metadynamics, machine learning,
 deep learning, free-energy perturbations, molecular modeling, etc.   

We are seeking highly qualified candidates with expertise in the development 
and/or application of computational biophysics/chemistry tools for structural
 biology and drug discovery. We are open to considering candidates with 
different seniority levels. The position will provide an opportunity to 
participate in various interdisciplinary projects, with a chance to work 
closely with experimental collaborators. Current research in the Filizola 
Lab spans a broad range of projects, including: (i) Characterizing 
transient conformational states of biomolecular complexes via integrative 
and information-driven modeling, (ii) Discovering novel chemotypes/biologics 
for various prominent drug targets by harnessing the power of machine learning and 
deep learning, (iii) Elucidating the atomic, kinetic, and thermodynamic determinants 
of drug efficacy at GPCRs, (iv) Advancing our understanding of IIb3 and V3 
activation and ligand-binding to enable the discovery of improved therapeutics; 
(v) Leveraging large-scale patient and genomic datasets to uncover and prioritize
 multi-target therapeutic opportunities.
 
The ideal candidate should have a Ph.D. or equivalent degree in a quantitative 
science major, including but not limited to Physics, Chemistry, Biophysics, 
Bioinformatics, Theoretical/Computational Chemistry, Computational Biology, 
Computer Science, Engineering, or a related discipline. To qualify for this 
position, strong analytical ability is required alongside expert programming 
skills and solid knowledge of one or more of the following: molecular dynamics 
simulations, free energy calculations, machine learning/deep learning, Markov 
State Models, virtual screening, docking, pharmacophore analysis, etc. Strong 
communication skills and the ability to collaborate with peers and train junior 
colleagues effectively are also required. The position is available immediately.

Qualified applicants should send a CV and at least 2 reference names by 
email to Dr. Marta Filizola at marta.filizola**mssm.edu. Review of 
applications will begin immediately and continue until the position is 
filled.