Team Lead - Drug Discovery

Position Overview

We are seeking a highly skilled and motivated Team Leader with expertise in AI-driven drug discovery, deep learning, and computational chemistry to lead a cross-disciplinary research team. The successful candidate will guide the design, development, and application of advanced AI / ML models for accelerating drug discovery, molecular design, and therapeutic development. This role requires both technical leadership and strategic vision to drive innovation in pharmaceutical R&D.

Key Responsibilities

• Leadership & Strategy

o Lead, mentor, and grow a team of AI scientists, computational chemists, and data engineers.

o Define research strategy and align project milestones with organizational drug discovery goals.

o Collaborate with medicinal chemists, biologists, and clinicians to integrate AI solutions into discovery pipelines.

o Develop and apply cutting-edge deep learning models (e.g., graph neural networks, generative models, foundation models) for molecular property prediction, de novo drug design, and protein–ligand interactions.

o Utilize computational chemistry techniques (docking, molecular dynamics, QSAR, free energy perturbation, ADME / Tox modeling) to validate AI predictions.

o Design workflows combining AI + physics-based methods to accelerate candidate selection.

o Stay current with advancements in AI for drug discovery, cheminformatics, and molecular simulations.

o Act as a bridge between computational and experimental teams to ensure smooth translation of AI insights into laboratory validation.

o Collaborate with external partners, academic institutions, and consortia.

o Present findings and strategy updates to leadership, stakeholders, and scientific committees.

o Oversee data management, curation, and integration from chemical, biological, and clinical sources.

o Ensure reproducibility, scalability, and regulatory compliance in AI-driven workflows.

o Drive publications, patents, and intellectual property creation in the AI drug discovery space.

Qualifications

o 7+ years of experience in AI / ML for drug discovery or computational chemistry, including at least 2–3 years in a leadership role.

o Strong track record of applying deep learning models (transformers, GNNs, generative models) to drug discovery problems.

o Experience with drug design platforms, cheminformatics toolkits (RDKit, OpenEye, Schrodinger, MOE), and molecular simulation software.

o Proven ability to manage multi-disciplinary teams and deliver on complex R&D projects.

o Expertise in Python, PyTorch / TensorFlow, Scikit-learn, DeepChem.

o Strong background in computational chemistry methods and molecular modeling.

o Knowledge of cloud computing (AWS, GCP, Azure) and high-performance computing environments.

o Strong leadership, project management, and mentoring abilities.

o Excellent communication and collaboration skills.

o Strategic mindset with a passion for innovation in healthcare.

Preferred Attributes