Scientist (Computational Chemistry / Structural Biology & Biomolecular Modeling)

**Join us and contribute to the discovery of medicines that will impact lives**:
**Hyderabad, India | Hybrid | Full-Time**:
**About Aganitha**:
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 near future, 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.

**Key Responsibilities**:

- Perform Molecular Dynamics (MD) simulations and Quantum Mechanics (QM) calculations to deeply understand biomolecular interactions (protein-ligand, lipid-protein, lipid-nucleic acid interactions, etc.), support small molecule or PROTAC design, facilitate catalyst design for chemical reactions, investigate complex chemical reaction mechanisms, and conduct polymorph screening.
- Define appropriate data models and identify relevant features for developing AI/ML-based models for predicting crucial properties such as ADMET (Absorption, Distribution, Metabolism, Excretion, Toxicity) profiles, lattice energies, reaction yields, and selectivity.
- Understand, analyze, critique, and implement cutting-edge research, effectively tailoring the approaches to specific problem contexts.
- Develop clear, concise, and compelling narratives of data-driven analyses performed using QM or MD techniques, making complex findings accessible.
- Effectively articulate and communicate intricate domain knowledge to a cross-functional team. Actively participate in requirements gathering, design discussions, and solution demonstrations.

**Qualifications**:

- PhD in Computational Chemistry, Cheminformatics, Structural Biology, Biochemistry, Biophysics, or a closely related field, coupled with a genuine passion for continuous learning.
- Strong interest in computational and data-driven methods with a clear understanding of how _in silico_ approaches can significantly accelerate drug discovery and development processes.
- Must possess a keen understanding of the interface of computer technology, high-throughput sciences, and chemistry/biology.
- Demonstrated experience with computational tools and techniques commonly used in structural biology and biomolecular modeling (e.g., protein-ligand docking, protein-protein interaction studies, homology modeling).
- Prior experience in the Biopharma industry is a plus.

**Desired Technical Skills/Expertise**:

- Hands-on experience with molecular dynamics software packages (e.g., GROMACS, NAMD, AMBER, CHARMM,OpenMM, etc.).
- Familiarity with quantum chemistry software (e.g., PySCF, ORCA, NWChem, Quantum Espresso, etc.).
- Proficiency in at least one scripting/programming language, preferably Python, for data analysis, automation, and workflow development.
- Understanding of biomolecular docking and virtual screening methodologies.
- Exposure to data visualization tools for scientific data.

**Added Advantages**:

- Expertise in computer programming (e.g., Python, C++, Fortran), including developing robust and reproducible code.
- Exposure to High-Performance Computing (HPC) environments, cloud computing platforms, and parallel computing techniques.
- Experience with database management in a scientific context.

**Soft Skills**:

- Excellent verbal and written communication skills are essential, with the ability to clearly articulate complex scientific and computational concepts to both technical and non-technical audiences.
- A proactive and collaborative attitude to work effectively within cross-functional teams, fostering an environment of shared learning and problem-solving.
- Strong problem-solving mindset, capable of independently identifying issues and proposing effective solutions.
- Proven interest and aptitude to break down large, complex problem statements into manageable and actionable work packets.
- Comfortable working effectively in a fast-paced, rapidly changing research and development environment.