Postdoc Computer-Driven Drug Discovery Technologies

Job Title: Postdoc Computer-Driven Drug Discovery Technologies

Job Number: 56752

Location: Los Angeles, US

Job Description

The Katritch lab invites applications for two NIH-funded postdoctoral positions at USC, Los Angeles. The positions will be affiliated with our new Center for New Technologies in Drug Discovery and Development (CNT3D), providing multidisciplinary computational, structural biology, and synthetic chemistry environment, with successful collaborations with disease experts on USC medical campus and across the world.

We are looking for highly talented and motivated researchers to join our team (http://katritch.usc.edu/ ) in developing and applying a new generation of molecular modeling and deep learning tools for predicting protein-ligand interactions, rational ligand design, and virtual ligand screening in Giga- and Terra-scale chemical spaces.  Successful applicants will focus on implementing Deep Learning methods complementing our V-SYNTHES approach (https://www.nature.com/articles/s41586-021-04220-9), and exploring new directions in computer-driven discovery as outlined in our recent Review (https://www.nature.com/articles/s41586-023-05905-z ).  We employ these state-of-the-art methods to discover ligands with new properties for neurobiology and potential clinical applications in the treatment of pain and addiction, inflammation, metabolic and neurodegenerative disease, and cancer.   Since the inception of the lab at USC in 2015, our work has been published in more than 70 high-impact papers, including 15 in Nature Journal. The positions are funded by NIH and internal USC grants, and offer highly competitive salaries, a vibrant interdisciplinary environment, and excellent opportunities for career development in both academia and industry.

Job Requirements 

We will consider two types of candidates for this position (a) strong computational chemists/molecular modelers willing to expand into deep learning applications and (b) experts in machine learning willing to apply their skills in drug discovery.  Successful candidates are expected to have:

– Ph.D. in computational chemistry / computational chemistry/ biophysics/ bioinformatics/ computer sciences or a related field 

– Demonstrated experience in structural bioinformatics, molecular modeling, computational chemistry and cheminformatics applications to drug design

– Programming and scripting skills  (Python and Linux shell is required, Pipelining, Knime

 and database management is a plus)

– Established record of high-quality scientific research and publications

– Strong analytical and problem-solving skills and scientific creativity are essential.

– Excellent verbal and written communication skills

An ideal candidate would also have one or two of the following skills:

– Expertise in deep learning (GCNN, 3D-CNN, generative models, proficiency in either pyTorch, TenzorFlow, MXNet, or other machine learning platform)

– Hands-on experience with at least one of the major drug discovery software packages (Molsoft ICM, Schrodinger, OpenEye)

– Demonstrated expertise in molecular dynamics studies of GPCRs and other membrane proteins 

The position is available immediately. Qualified applicants should send a CV and contact information for at least 3 references to Prof. Vsevolod “Seva” Katritch (katritch[a]usc.edu).

Please use the email subject “Postdoctoral Associate”. 

 Applications will be considered until the position is filled. 

Application Deadline: 2023-11-25