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.