About VantAI:
VantAI is building a computational pipeline combining state-of-the-art physics-based modeling and machine learning to revolutionize drug discovery and development. Working together with some of the worlds leading biopharmaceutical companies, we design, test, and optimize novel therapies to treat some of the worlds most difficult diseases.
Key Responsibilities:
Develop computational pipelines for target protein degradation (TPD), leveraging molecular dynamics, free-energy calculation, pharmacophore screening, pocket identification, docking, quantum mechanics, and homology modeling
Merge state-of-the-art
in silico
approaches with cutting-edge machine learning ( e.g. , deep learning, generative methods, reinforcement learning, topology)
Work collaboratively with experts from other fields ( e.g. , computational biology, molecular biology, medicinal chemistry, machine learning) to drive harmonized models with innovative features
Basic Qualifications:
MS/PhD degree in Chemistry, Biochemistry, Computational Chemistry, Chemical Engineering, or other related subject
Minimum 2 years of post graduate experience in the pharmaceutical industry or academia applying various computational modeling methods to drug discovery projects
Experience with protein-protein interaction studies (protein associations, protein-peptide interactions, target protein degradation) using computational tools, e.g. LightDock, HADDOCK, RosettaDock, PIPER, AutoDock CrankPep, coarse-grained molecular dynamics (CGMD) or Brownian dynamics (BD)
Track record of developing new methods, tools, or programs in or related to computational chemistry
Strong coding skills strong experience with Python in large, git-controlled code bases is a must, C & Fortran is a plus
Preferred Qualifications:
Open Source contribution and maintenance track record, such as starting and maintaining computational pipelines
A solid understanding of deep learning based frameworks in structure-based domains, e.g. GNINA, KDEEP, EquiBind, dMaSIF
Experience in leveraging experimental data for refining computational models of protein complexes, e.g. SID, HDX-MS
Strong backgrounds of binding free-energy methods, e.g. alchemical approach using SDM/DDM, physical pathway methods
Quick and scrappy learner who adapts well to a fast-moving environment and gets things done, combining creativity, problem-solving skills, and a can-do attitude to overcome obstacles
Understanding of business problems and how to build end-to-end analytics use cases tied to business value
Ability to provide thought leadership by researching best practices, conducting experiments, and collaborating with industry leaders
Excellent written and verbal communication skills along with a strong desire to work in cross-functional teams
Salary: $120,000 - $180,000
This band is a reflection of the job description as written. Looking for a higher salary? Apply anyway! We are happy to speak to more experienced candidates who may require a higher salary and discuss that experience in our first touchpoint.
#J-18808-Ljbffr