Computational Chemistry / Physics Scientist – AI Drug Discovery & Quantum Sensing
Gopal K. Saxena Center for Advanced Research (GSCAR) · Bengaluru, Karnataka, India
Apply & track with Apply EdgeComputational Chemistry / Physics Scientist – AI Drug Discovery & Quantum Sensing
- 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 MethodsDepending 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 representationsSoftware and ProgrammingExperience with some of the following would be valuable:Chemistry / Molecular ModelingGaussian, ORCA, GAMESS, GROMACS, AMBER, AutoDock/Vina, RDKit, PyMOL, VMD, MultiwfnAI / Data SciencePython, PyTorch, TensorFlow, scikit-learn, DeepChem, pandas, NumPyComputational InfrastructureLinux, HPC clusters, GPUs, Git, Docker, workflow automationExperience 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.PreferredExperience 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 computingKey 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.