Team Lead - R & D Materials

Prescience Insilico; Bengaluru; Presencial; INR 4.000.000 - 7.000.000; Jornada completa

Descripción de la vacante

Prescience Insilico in Bengaluru seeks a highly motivated Team Lead to guide a multidisciplinary team of Research Scientists in Computational Chemistry, Materials Science, Molecular Modelling, and AI/ML-driven research.

You will mentor team members, drive research programs, manage customer engagements, and contribute to product development and platform enhancements, while ensuring timely delivery of high-quality scientific outcomes.

Formación

• Ph.D. or equivalent in a relevant scientific field is required.
• 3–6 years of experience in computational chemistry or materials science with leadership exposure.
• Strong publication and project-management experience are preferred.

Responsabilidades

• Contribute hands-on to projects, lead projects, and manage a 3-5 members team of Research Scientists.
• Provide scientific guidance on molecular simulations and ML-augmented workflows.
• Review methodologies, results, publications, and deliverables.
• Drive innovation and identify new research directions aligned with company goals.
• Contribute to architecture, development, and enhancement of Prescience Products and platforms.
• Plan, execute, and oversee multiple R&D projects simultaneously.
• Ensure timely delivery of customer projects with scientific rigor.
• Coordinate with customers, collaborators, and internal stakeholders.
• Track progress, resources, and risk mitigation.

Conocimientos

Python

C/C++

Shell scripting

Team leadership

HPC environments

Customer engagement

Educación

Ph.D. in Computational Chemistry, Materials Science, Chemical Engineering, Computational Physics, or related fields

Herramientas

GROMACS

LAMMPS

Quantum Espresso

Descripción del empleo

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.

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

We are seeking a highly motivated and experienced Team Lead to lead a multidisciplinary team of Research Scientists working in Computational Chemistry, Materials Science, Molecular Modelling, and AI/ML-driven scientific research.

The ideal candidate will combine strong scientific expertise with leadership capabilities to drive research programs, mentor team members, manage customer engagements, and contribute to the strategic growth of Prescience Insilico's products and services. The role involves leading cutting-edge research projects, guiding development of products and platforms, collaborating with industry and academic partners, and ensuring successful delivery of high-quality scientific outcomes.

Responsibilities

• Contribute hands-on to projects, lead projects, and manage a 3-5 members team of Research Scientists working on computational chemistry, materials science, and AI/ML-based research projects.
• Provide scientific and technical guidance on molecular simulations, machine learning models, and computational workflows.
• Review research methodologies, simulation results, publications, and project deliverables.
• Drive innovation and identify new research directions aligned with company objectives.
• Contribute to the architecture, development, and enhancement of Prescience Products and platforms.
• Plan, execute, and oversee multiple R&D projects simultaneously.
• Ensure timely delivery of customer projects while maintaining scientific quality and rigor.
• Coordinate with customers, academic collaborators, and internal stakeholders.
• Track project progress, resource allocation, and risk mitigation.
  

Requirements

• Ph.D. in Computational Chemistry, Materials Science, Chemical Engineering, Computational Physics, or related fields.
• 3-6 years of relevant experience (preferably 1-2 years in industry) in Computational Chemistry, Materials Science, Molecular Modelling, AI/ML, or related scientific domains.
• Prior experience leading research teams, mentoring scientists, or managing technical R&D projects.
• Strong expertise in molecular simulation methods such as Molecular Dynamics, Monte Carlo, Mesoscale Simulations, and related computational techniques.
• Deep understanding of polymers, complex fluids, surfactants, biomolecules, and molecular systems.
• Hands-on experience with molecular modelling and simulation software such as GROMACS, LAMMPS, Quantum Espresso, or similar tools.
• Experience applying Machine Learning and Deep Learning techniques to materials science and molecular modelling problems.
• Strong programming skills in Python, C/C++, and Shell Scripting.
• Experience in reviewing scientific research, simulation methodologies, technical reports, and publications.
• Proven ability to interact with customers, understand scientific requirements, and deliver technical solutions.
• Experience in High-Performance Computing (HPC) environments.
• Ability to plan, execute, and manage multiple projects simultaneously while maintaining high scientific standards.
• Experience in software deployment, installation, troubleshooting, and debugging on Workstations, HPC clusters, and Servers is preferred.