Application Scientist – Computational Chemistry/Materials Science
Actively Reviewing the ApplicationsPrescience Insilico
India, Karnataka
Full-Time
On-site
INR 12–18 LPA
Posted 3 days ago
•
Apply by June 3, 2026
Job Description
About The Job
Only apply if you are trained in Computational Chemistry/Materials Science/Computation Biology. Your application will be selected if you have carried out projects, done your PhD or have experience working in these areas.
About Us
At Prescience Insilico, we are at the forefront of innovation in scientific software solutions. We specialize in creating cutting-edge software tools tailored for the R&D in the Life Science and Materials Science industries and academia. Our mission is to empower researchers, scientists, and institutions with the tools they need to accelerate discoveries and breakthroughs in these critical fields. We also collaborate with the pharma, materials, chemical, and energy industries to accelerate their R&D through AI/ML and computational modeling and simulations.
Job Description
The role requires a deep understanding of Computational Chemistry and Materials Science in the domain of complex fluids, polymers, and biomolecules. You will be working on R&D projects using cutting-edge particle-based computational methods, performing independent research, and delivering research projects to our customers. You will also be responsible for the development of PRinS3 platform and promoting the platform by giving presentations and demos of the platform to academia and industry. This role also involves working on publication-quality research work in collaboration with colleagues, customers, or others.
Required
Only apply if you are trained in Computational Chemistry/Materials Science/Computation Biology. Your application will be selected if you have carried out projects, done your PhD or have experience working in these areas.
About Us
At Prescience Insilico, we are at the forefront of innovation in scientific software solutions. We specialize in creating cutting-edge software tools tailored for the R&D in the Life Science and Materials Science industries and academia. Our mission is to empower researchers, scientists, and institutions with the tools they need to accelerate discoveries and breakthroughs in these critical fields. We also collaborate with the pharma, materials, chemical, and energy industries to accelerate their R&D through AI/ML and computational modeling and simulations.
Job Description
The role requires a deep understanding of Computational Chemistry and Materials Science in the domain of complex fluids, polymers, and biomolecules. You will be working on R&D projects using cutting-edge particle-based computational methods, performing independent research, and delivering research projects to our customers. You will also be responsible for the development of PRinS3 platform and promoting the platform by giving presentations and demos of the platform to academia and industry. This role also involves working on publication-quality research work in collaboration with colleagues, customers, or others.
Required
- M. Sc/PhD in Computational Chemistry, Material Science and similar fields
- PhD or experience should be in the development and use of Machine Learning for materials and molecular simulation methods like molecular dynamics, Monte Carlo, Mesoscale Simulations for polymers, complex fluids, surfactants, and molecular systems.
- Hands-on experience in using machine learning, deep learning methods and molecular modeling software like GROMACS, LAMMPS, Quantum Espresso etc.
- Excellent presentation skills and fluency in English
- Programming skills - Python, C/C++, Shell Scripting
- Experience with machine learning algorithms is required
- 1-2 years of experience working in industry or as a post-doc will be a plus
- Skilled in presentations/Demo
- Experience in High Performance Computing and Cloud Computing is a plus
- Skilled to install software on Workstation/HPC/Server, debug technical issues
- Ability to travel alone across India
- Ability to work flexible hours
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