Scientist (QM applications for Catalysis & Materials)

Aganitha Cognitive Solutions; Hyderabad; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

Aganitha Cognitive Solutions is seeking a PhD-level computational scientist to lead high-throughput modeling of chemical reactions, catalysis, and materials. You will design and execute simulations, analyze outcomes, and collaborate with clients to translate insights into scalable R&D solutions.

The role spans organometallics, biocatalysis, polymers, and self-assembly, leveraging AI/ML for screening and prediction and contributing to publications or patents where applicable.

Qualifications

• PhD in computational chemistry, chemical physics, materials science, polymer/surfactant science, soft matter physics, or related fields required for research roles;

Responsibilities

• Execute simulations using DFT, ab initio quantum chemistry, QM/MM, periodic and non-periodic quantum methods, and molecular dynamics to study reaction pathways, transition states, catalytic mechanisms, molecular interactions, stability, and self-assembly in systems such as organometallics, enzymes, crystalline materials, surfactants, polymers, colloids, and biomolecules.
• Apply computational methods to support molecular and materials design for applications including semiconductors, greenhouse gas capture, and formulations, and investigate interactions between components (e.g., surfactants with skin, hair, or fabrics).
• Interpret simulation outputs and extract descriptors or features for AI/ML models; validate insights with experimental data, contribute to ligand/material design, stay current with literature, and support publications or patents.

Skills

Python

Fortran

C++

Julia

Education

PhD in Computational Chemistry or related field

Tools

Gaussian

ORCA

VASP

Quantum ESPRESSO

CP2K

NAMD

AMBER

LAMMPS

GROMACS

PySCF

SIESTA

OpenMM

Job description

Scientist (QM applications for Catalysis & Materials)

Join us and contribute to the discovery of medicines that will impact lives!

Accelerate drug discovery and development for Biopharma and Biotech R&D with in silico solutions leveraging Computational Biology & Chemistry, High throughput Sciences, AI, ML, HPC, Cloud, Data, and DevOps.

In silico solutions are transforming the biopharma and biotech industries. Our cross-domain science and technology team of experts embark upon and industrialize this transformation. We continually expand our world-class multi-disciplinary team in Genomics, AI, and Cloud computing, accelerating drug discovery and development. What drives us is the joy of working in an innovation-rich, research-powered startup bridging multiple disciplines to bring medicines faster for human use. We are working with several innovative Biopharma companies and expanding our client base globally. Read about how and what solutions we build .

Aganitha (अगणित): “countless” or “limitless” in Sanskrit serves as a reminder and inspiration about the limitless potential in each one of us. Come join us to bring out your best and be limitless!

Role Overview

High-throughput experimentation, computational & data-driven modeling, and the advent of the Open Science era are fundamentally transforming research, discovery, and development across diverse industries. Aganitha is at the forefront of co-innovation with global clients, shaping next-generation R&D ( aganitha.ai ). While our primary client base has been in global Biopharma, we are actively expanding our collaborations into consumer brands and in the materials design industry.

You will collaborate closely with research leaders at our client organizations, identifying their needs and designing innovative solutions. Working with our internal technical and scientific teams, you will drive solutions from concept to launch and growth. You may also interact with external vendors to coordinate experimental validation of the in silico solutions developed at Aganitha.

To excel in this role, you must possess a strong interest in engaging with customers to apply the latest scientific and technological advancements for R&D acceleration, thereby contributing to Aganitha’s growth.

Aganitha is looking for a computational scientist. The core of this role involves applying advanced modeling to chemical reactions, catalysis, materials, and soft matter systems, spanning organometallics, bio-catalysis, polymers, and self-assembly processes.

Key Responsibilities

• Execute simulations using DFT, ab initio quantum chemistry, QM/MM, periodic and non-periodic quantum methods, and molecular dynamics to study reaction pathways, transition states, catalytic mechanisms, molecular interactions, stability, and self-assembly in systems such as organometallics, enzymes, crystalline materials, surfactants, polymers, colloids, and biomolecules.
• Apply computational methods to support molecular and materials design for applications including semiconductors, greenhouse gas capture, and formulations (e.g., skin care ingredients, pharmaceutical excipients), and investigate interactions between components (e.g., surfactants with skin, hair, or fabrics).
• Interpret simulation outputs (e.g., RDFs, binding energies, density profiles) and extract descriptors or features for AI/ML models; validate insights with experimental data, contribute to ligand/material design, stay current with literature, and support publications or patents.

Required Qualifications

PhD in computational chemistry, chemical physics, materials science, polymer/surfactant science, soft matter physics, or related fields required for research roles;

Demonstrated research experience in computational modeling of chemical reactions, catalysis, materials, or soft matter systems. Examples may include:

• Reaction mechanism and transition state modeling using DFT or ab initio quantum chemistry (e.g., organometallic catalysis, enzyme catalysis, reaction pathways).
• Computational studies of heterogeneous catalysis or materials properties using periodic electronic structure methods (e.g., adsorption, surface reactions, defect chemistry in catalytic or semiconductor materials).
• Molecular dynamics or QM/MM simulations of biomolecular or soft matter systems (e.g., enzymes, proteins, polymers, surfactants, or colloidal assemblies).
• Modeling of intermolecular interactions and self-assembly processes in complex formulations (e.g., surfactant micelles, polymer networks, or biomolecular complexes).
• Free energy calculations, enhanced sampling, or statistical mechanics approaches to understand molecular stability, binding, or phase behavior.

Evidence of strong research output through peer-reviewed publications, conference presentations, or patents in computational chemistry, catalysis, materials modeling, or related areas is highly desirable.

Technical Skills

• Proficiency with computational chemistry and molecular simulation software such as Gaussian, ORCA, VASP, Quantum ESPRESSO, CP2K, CPMD, NAMD, AMBER, LAMMPS, GROMACS, PySCF, SIESTA, OpenMM, or similar tools for electronic structure calculations, molecular dynamics, and hybrid modeling.
• Programming experience in Python, Fortran, C++, or Julia for workflow automation, data analysis, visualization, and HPC workflows on clusters or GPUs.
• Strong understanding of quantum mechanics, statistical thermodynamics, reaction kinetics, free energy calculations, and high-throughput computational screening.

Added Advantages

• AI/ML familiarity (e.g., PyTorch, scikit-learn) for screening and prediction.
• Experience in reaction mechanism studies and catalysis research.
• Experience with enhanced sampling techniques (e.g., ab-initio MD, metadynamics, umbrella sampling).
• Expertise in advanced HPC/GPU parallelization.
• Postdoctoral experience

Soft Skills

• Strong communication skills with the ability to simplify complex scientific concepts for cross-functional teams.
• Collaborative and adaptable mindset with strong analytical and critical thinking in fast-paced research environments.