Computational Chemistry / Physics Scientist – AI Drug Discovery & Quantum Sensing

Computational Chemistry / Physics Scientist – AI Drug Discovery & Quantum Sensing

Location: Bangalore, India

Employment Type: Full-time

Experience: 1–2 years

Department: Computational Science / R&D

Key Responsibilities

AI-Driven Drug Discovery

• Develop and apply computational approaches for drug discovery and molecular design.
• Perform molecular docking, molecular dynamics simulations, free-energy calculations, and binding-energy analysis.
• Develop machine-learning and deep-learning models to predict molecular properties, activity, toxicity, and ADMET.
• Work with chemical and biological datasets and develop meaningful molecular descriptors and representations.
• Apply cheminformatics and AI methods for virtual screening, hit identification, lead optimization, and candidate prioritization.
• Integrate physics-based simulations with machine-learning models to improve prediction reliability and interpretability.
• Explore generative AI and molecular-generation approaches for designing new drug-like molecules.
• Collaborate with medicinal chemists, biologists, experimental scientists, and software/AI engineers.

Quantum Sensor and Materials Modelling

• Perform quantum-mechanical calculations to understand molecular and materials properties relevant to quantum sensing.
• Study electronic structure, spin states, magnetic properties, molecular orbitals, hyperfine interactions, and other properties relevant to quantum sensors.
• Model molecular systems and functional materials designed for sensing magnetic, electric, chemical, thermal, or environmental changes.
• Investigate interactions between sensing molecules/materials and their surrounding environment.
• Use computational modeling to support the design and optimization of spin-active molecules, defects, radicals, and hybrid quantum-sensing platforms.
• Establish relationships between molecular structure, electronic/spin properties, and measurable sensor response.
• Work closely with experimental teams to guide material synthesis, characterization, and sensor development.

Computational Methods

Depending on the project, the scientist may work with:

• Quantum chemistry and electronic-structure calculations
• DFT, TD-DFT, Hartree–Fock, MP2 and ab initio methods
• QM/MM and multiscale modeling
• Molecular dynamics simulations
• Free-energy calculations and enhanced-sampling methods
• Molecular docking and virtual screening
• Machine learning and deep learning
• Cheminformatics and molecular representations

Software and Programming

Experience with some of the following would be valuable:

Chemistry / Molecular Modeling

Gaussian, ORCA, GAMESS, GROMACS, AMBER, AutoDock/Vina, RDKit, PyMOL, VMD, Multiwfn

AI / Data Science

Python, PyTorch, TensorFlow, scikit-learn, DeepChem, pandas, NumPy

Computational Infrastructure

Linux, HPC clusters, GPUs, Git, Docker, workflow automation

Experience with quantum-computing or quantum-simulation frameworks is an advantage but is not mandatory.

Qualifications Required

• PhD or Master's degree in Computational Chemistry, Theoretical Chemistry, Computational Physics, Physics, Chemical Engineering, Materials Science, Pharmaceutical Sciences, or a closely related field.
• Strong understanding of computational chemistry or computational physics.
• Practical experience with Python and scientific programming.
• Experience with at least one major area such as molecular modeling, quantum chemistry, molecular dynamics, cheminformatics, or machine learning.
• Ability to independently analyze computational results and communicate findings clearly.

Preferred

Experience in one or more of the following areas:

• AI/ML for drug discovery
• Structure-based drug design
• DFT, Molecular dynamics, and free-energy calculations
• QM/MM simulations
• Quantum chemistry of radicals or spin systems
• Magnetic-resonance-related calculations
• Quantum sensing
• Defect or spin-centre modeling
• AI-assisted molecular design
• High-performance computing

Key Skills

• Computational problem solving
• Molecular and electronic-structure modeling
• AI/ML and data analysis
• Scientific programming in Python
• Interpretation of complex computational datasets
• Scientific communication and technical documentation
• Ability to work independently and as part of a multidisciplinary team
• Strong interest in translating computational research into real-world applications.