Medvolt- Research Associate - Computational Chemistry (AI-Integrated Drug Discovery)

About Medvolt

Medvolt is a deep-tech biotechnology company building AI-driven products to transform drug discovery and biomedical research. Our platforms integrate artificial intelligence, large-scale data, and physics-based simulations to enable faster and more reliable discovery workflows.

We are building modular, scalable products that allow users to run complex scientific workflows, interact with AI systems, and manage compute seamlessly.

Role Overview

We are looking for a Research Associate - Computational Chemistry to drive domain-focused modeling, AI/ML integration, and execution of computational pipelines within Medvolt's products.

This role focuses on:

computational chemistry workflows and simulations

domain-specific AI/ML model components

execution and validation of pipelines with QA/QC

deriving insights from computational experiments

You will work at the intersection of chemistry, biology, and AI to design, evaluate, and improve computational strategies for drug discovery.

What You'll Work On

Designing and executing computational chemistry workflows across drug discovery pipelines

Running and analyzing docking, molecular dynamics, and simulation-based experiments

Building and contributing to domain-specific AI/ML components for chemical and biological systems

Performing QA/QC on computational outputs and ensuring robustness of results

Interpreting experimental results and deriving actionable insights

Identifying limitations in current approaches and proposing improvements

Working across both small molecule and large molecule (protein/enzyme) systems

Collaborating with AI, backend, and domain teams to integrate workflows into scalable systems

Key Responsibilities

Execute end-to-end computational chemistry pipelines including docking, MD simulations, and analysis

Develop and refine domain-specific AI/ML components for modeling and prediction

Perform rigorous QA/QC on computational experiments and outputs

Analyze results and generate insights for lead identification and optimization

Propose and implement improvements in computational workflows an methodologies

Work with modern computational chemistry and molecular modeling tools

Collaborate with cross-functional teams to integrate pipelines into product systems

Document workflows, results, and best practices for reproducibility

Tech Stack

Computational Chemistry: Docking tools, molecular modeling suites, cheminformatics toolkits

Simulation: GROMACS, OpenMM, Desmond or similar MD platforms

Cheminformatics: RDKit, Open Babel

Protein / Large Molecule (Preferred): Structure analysis, protein-ligand and protein-protein systems

Programming: Python (NumPy, Pandas, scientific computing libraries)

AI/ML (Exposure): ML/DL frameworks, domain-specific modeling approaches

Other: Data analysis, visualization, and workflow tools

What We're Looking For

Core Domain Expertise

Strong foundation in computational chemistry and molecular modeling

Hands-on experience with docking, molecular dynamics, and simulation workflows

Understanding of drug discovery pipelines including hit identification and optimization

Experience working on both small molecule and exposure to large molecule systems

AI/ML Integration (Important)

Experience working with or contributing to AI/ML models in chemistry or biology

Understanding of how computational chemistry workflows integrate with AI-driven systems

Ability to build or contribute to domain-specific modeling components

Experimental Thinking & Analysis

Ability to design computational experiments and interpret results critically

Strong analytical skills to derive insights and propose improvements

Experience performing QA/QC on computational outputs