Aganitha Jobs – Bioinformatics, Computational Biology, Biomedical Engineering, Biophysics Eligible
Post I
Scientist (AI Modeling for Computational Sciences)
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.
As a Scientist at Aganitha, you will be instrumental in leveraging cutting-edge advances in computational chemistry, materials science, soft matter physics, AI/ML, and high-performance computing in the Cloud. You will contribute to accelerating design and development across a spectrum of applications, including but not limited to: small molecule therapeutics, biologics, gene, cell & RNA therapies within Biopharma; new product formulations for consumer brands; and novel materials for various industrial applications.
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.
Key Responsibilities
- Design and develop AI/ML models to solve complex problems, such as predicting molecular properties, material behaviors, or reaction outcomes.
- Curate, process, and analyze scientific datasets from various sources, including literature and experimental data, ensuring data quality and readiness for model training.
- The candidate should be skilled in analyzing high-throughput omics datasets such as single-cell, spatial, and genomic data, and in computational modeling of biological systems, including network and pathway analysis. They should also have expertise in the in-silico design and optimization of therapeutic candidates such as antibodies, RNA molecules, and viral vectors. Proficiency in bioinformatics tools, biological databases, and the application of AI/ML approaches for biological data analysis and predictive modeling is essential.
- Develop intelligent featurization strategies that accurately represent chemical structures, physical properties, or biological interactions, drawing upon your scientific understanding.
- Implement, train, and evaluate cutting-edge Machine Learning and Deep Learning algorithms (e.g., CNNs, RNNs, LSTMs, Transformer architectures) to build robust predictive models.
- Rigorously validate models against client-provided data and established benchmarks, ensuring their accuracy, generalizability, and utility.
- Translate complex technical and scientific findings into clear, actionable insights for both technical and non-technical stakeholders.
- Collaborate effectively with computational chemists, data scientists, and wet lab scientists to define project requirements, iterate on solutions, and ensure successful deployment.
- Stay abreast of the latest advancements in AI/ML, computational chemistry, and relevant scientific domains, continuously seeking opportunities to apply new methodologies.
Qualifications
- PhD, post-doctoral research, or equivalent higher studies in Computational Chemistry, Cheminformatics, Materials Science, Chemical Engineering, Biochemistry, Computational Biology, Bioinformatics, Computational Physics, Medicinal Chemistry, Applied Mathematics, Applied Statistics, Fluid Dynamics or a closely related scientific discipline.
- Familiarity with one or more of the following core domain skills: High-throughput docking and QSAR studies, Atomistic or Coarse-grained Molecular Dynamics (including Enhanced MD using PLUMED, Langevin Dynamics, Brownian Dynamics, and Dissipative Particle Dynamics), Periodic or non-periodic Quantum Chemical Calculations, Ab initio MD simulations and QM/MM simulations, Cheminformatics using RDKit, Mathematical Modeling, or Computational Fluid Dynamics.
- Strong foundational understanding of the scientific principles underlying computational chemistry, materials science, or related fields (e.g., colloidal chemistry, polymer science, surfactant chemistry, soft condensed matter physics, etc.).
- Solid mathematical intuition of Machine Learning algorithms, including Deep Learning architectures such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), LSTMs, and Transformer architectures.
- Proficiency in modular, typed, and object-oriented Python programming.
- A high-level understanding of the ML/DL project lifecycle, from data preparation and feature engineering through model development, training, evaluation, and deployment.
- Excellent problem-solving skills and the ability to apply critical thinking to complex scientific and technical challenges.
- Strong verbal and written communication skills, with the ability to effectively communicate technical concepts to diverse audiences.
Nice to Have
- Experience in effectively building and deploying ML solutions using popular frameworks such as PyTorch, TensorFlow, Keras, or scikit-learn.
- Proficiency in shell scripting.
- Proficiency in working with Linux-based operating systems (e.g., Ubuntu, Fedora, CentOS, Debian).
Big Plus
- Exposure to large language models (LLMs) such as ChatGPT, Claude, or Gemini, and practical experience in utilizing such tools for day-to-day work (e.g., writing research reports, understanding new concepts, generating code).
- Experience in optimal usage of High Performance Computing (HPC) resources.
- Familiarity with container-based usage of software and their dependencies (e.g., Docker).
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Post II
Biomedical Image Analysis Scientist
Join us and contribute to the discovery of medicines that will impact lives!
Hyderabad, India
About Aganitha
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!
Key Responsibilities
- Design, implement, and optimize algorithms for biomedical image analysis using deep learning and computer vision techniques (CNNs, transformers, diffusion models, etc.).
- Work on multi-modal datasets — including cellular images, microscopy, MRI, CT, EEG, ECG and histopathology slides — to extract meaningful biological or clinical insights.
- Develop automated image & waveform segmentation, classification, and feature extraction workflows.
- Collaborate with biologists, chemists, and AI engineers to integrate imaging data with omics and molecular datasets.
- Contribute to building scalable pipelines for image data preprocessing, model training, and deployment.
- Validate models against experimental data and ensure reproducibility of results.
- Stay current with advances in biomedical imaging, AI/ML architectures, and data integration methods.
Required Skills & Experience
- Strong background in Biomedical Engineering, Computer Science, Electrical Engineering, Biophysics, Computational Biology, or related field.
- PhD or Master’s degree with experience in biomedical image analysis or computer vision.
- Hands-on experience with Python, PyTorch (or TensorFlow), OpenCV, and scikit-image.
- Experience with microscopy, histopathology, and radiology image datasets.
- Knowledge of image preprocessing, segmentation, and 3D/volumetric data handling.
- Familiarity with data annotation, weak supervision, or multi-modal learning is a plus.
- Excellent communication and problem-solving skills.
Educational Qualifications
- Prior experience integrating image data with omics, clinical, or molecular datasets.
- Experience deploying ML models or using MLOps tools (e.g., MLFlow, ClearML).
- Publications or open-source contributions in biomedical imaging or computational biology.
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Post III
Customer Solutions Manager
Join us and contribute to the discovery of medicines that will impact lives!
Hyderabad, India
About Aganitha
High-throughput experimentation, Computational & Data-driven modeling and the dawn of the Open Science era are dramatically changing how BioPharma researches, discovers and develops new therapeutics. Aganitha is co-innovating with global biopharma customers on next generation R&D.
As a Customer Solutions Manager at Aganitha, you will be called upon to blend advances in multiple disciplines such as Omics, Structural Biology, Protein and Antibody Engineering, Computational Quantum Chemistry, AI/ML, and High-performance computing in the Cloud to help our global BioPharma customers accelerate design and development of SMOL, Antibody, Gene, Cell & RNA therapeutics. You will work with research leaders at our customer organizations, identify their needs and build solutions in collaboration with our internal technical and scientific teams.
To succeed in this role, you must have a strong interest in engaging with customers to apply the latest scientific and technology advances for R&D acceleration, driving revenue growth for Aganitha in the process.
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!
Key Responsibilities
To succeed in this role, you must have a strong interest in engaging with customers to apply the latest scientific and technological advances for R&D acceleration, driving revenue growth for Aganitha in the process.
- Use your life sciences expertise to define in silico solutions for addressable areas and pain points in disease research, drug discovery, and development processes, in close collaboration with prospects, customers, partners, and the multi-disciplinary team at Aganitha.
- Interact with scientists, directors, and VPs of global Biopharma, interpret their needs/asks, and define and refine solutions that will address them.
- Drive clarity and definition to the solutions being developed/created
- Create marketing content describing the capabilities of the solution, and communicate the same to the global biopharma scientists
- Drive the sales and marketing of various solutions and capabilities of Aganitha
Desired Skills / Expertise
- Ph.D. in Biology, Chemistry, Biotechnology, Bioinformatics, Cheminformatics (Life Sciences) with a passion to learn.
- Master’s degree with at least 2 years of industry experience in a Business Development team
- Strong interest in computational and data-driven methods and a clear understanding of how in silico methods can accelerate drug discovery and development processes. Must have a keen understanding of the interface of computer technology, high throughput sciences, and Biology/Chemistry.
- Strong interest in engaging with business aspects of pharma
- Strong verbal and written communication skills are a must
- Strong interest in engaging and communicating with customers
- You need to be comfortable working in a fast-paced, rapidly changing environment
- Your creativity, knowledge, and ability to prioritize will play a key role in your ability to fine-tune existing solutions, and/or help build new solutions.
- Prior experience in the Biopharma industry is a plus
- MBA/PGDM is a plus
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Post IV
Scientist (Computational Chemistry / Materials & Molecular 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.
As a Scientist at Aganitha, you will be instrumental in leveraging cutting-edge advances in computational chemistry, materials science, soft matter physics, AI/ML, and high-performance computing in the Cloud. You will contribute to accelerating design and development across a spectrum of applications, including but not limited to: small molecule therapeutics, biologics, gene, cell & RNA therapies within Biopharma; new product formulations for consumer brands; and novel materials for various industrial applications.
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.
Key Responsibilities
- Perform advanced computational simulations (e.g., Periodic and non-periodic Quantum Mechanics, Atomistic and/or Coarse-grained variants of Molecular Dynamics, Monte Carlo, Brownian Dynamics, Langevin Dynamics, Dissipative Particle Dynamics, etc.) to understand stability, complex interactions and design principles relevant to various hard and soft matter systems e.g., inorganic/organic crystalline materials, surfactants, polymers, colloids, biomolecules, etc.
- Apply computational methods to materials design for various applications such as semiconductor devices, capture and storage of greenhouse gases, skin and body care formulations, excipients, etc.
- Conduct molecular modeling studies to investigate self-assembly phenomena and interactions between various components in the formulation of a material, such as surfactant or polymer interactions with diverse substrates (e.g., skin, hair, fabric).
- Interpret results from domain-specific simulations (e.g., MD, DFT) and structure the scientific data into features or descriptors—such as radial distribution functions, binding energies, surface areas, or density profiles—relevant for downstream AI/ML modeling of material properties or formulation performance.
- Understand, analyze, critique, and implement research papers, tailoring approaches to specific problem contexts.
- Develop clear and concise narratives of data-driven analyses performed using computational techniques.
- Effectively articulate and communicate complex domain knowledge to cross-functional teams. Participate actively in requirements gathering, design discussions, and demonstrations.
- Continuously learn and stay up-to-date on emerging technologies and scientific advancements in computational chemistry, materials science, and related fields—research opportunities for applying advanced computational methods to evolving industry challenges.
Educational & Research Qualifications
- PhD, post-doctoral research, or equivalent higher studies in Computational Chemistry or Computational Physics applied to Materials Science, Polymer Science, Surfactant Science, Colloidal Chemistry, Soft Matter Physics, Fluid Dynamics, or a closely related field.
- Demonstrated first-hand research experience in problems in the domain of materials science, for example:
- Materials design for various applications such as semi-conductor devices, capture and storage of green-house gases, skin and body care formulations, excipients.
- Crystal structure prediction of inorganic/organic molecules
- Molecular/colloidal self-assembly and crystallization phenomena
- Interactions between various components in the formulation of a material, e.g., surfactant or polymer interactions with diverse substrates (e.g., skin, hair, fabric).
- Proficiency in at least one of the advanced computational chemistry methods viz. periodic and non-periodic Quantum Mechanics, Atomistic and/or Coarse-grained variants of Molecular Dynamics, Monte Carlo, Brownian Dynamics, Langevin Dynamics, Dissipative Particle Dynamics.
Technical Skills
- Familiarity with computational chemistry packages such as Quantum Espresso, VASP, LAMMPS, PySCF, GROMACS, NAMD, CP2K, SIESTA, OpenMM, or similar.
- Must have a keen understanding of the interface of computer technology, high-throughput sciences, and chemistry/materials science.
Added Advantages
- Familiarity with AI/ML methods and their application in scientific research.
- Expertise in computer programming (e.g., Python, C++, Fortran).
- Exposure to High-Performance Computing (HPC) environments and parallel computing.
Soft Skills
- Excellent verbal and written communication skills are essential.
- Excellent communication skills, with the ability to distill complex scientific concepts into easily understandable insights for diverse audiences.
- Right attitude to collaborate effectively within a cross-functional team environment.
- Ability to quickly grasp new scientific domains and apply critical thinking to novel challenges.
- Comfortable working in a fast-paced, rapidly changing environment.
- Strong interest and aptitude to break down large, complex problem statements into manageable work packets.
CLICK HERE TO APPLY
Post V
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.
As a Scientist at Aganitha, you will be instrumental in leveraging cutting-edge advances in computational chemistry, materials science, soft matter physics, AI/ML, and high-performance computing in the Cloud. You will contribute to accelerating design and development across a spectrum of applications, including but not limited to: small molecule therapeutics, biologics, gene, cell & RNA therapies within Biopharma; new product formulations for consumer brands; and novel materials for various industrial applications.
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.
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.
- Continuously learn and stay up-to-date on emerging technologies and scientific advancements in computational chemistry and structural biology. Research opportunities for the application of AI in the development of emerging therapeutic techniques.
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
- Familiarity with AI/ML methods and their application in scientific research, including areas like QSAR/QSPR, generative models for molecular design, or predictive analytics in drug discovery.
- 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.
- Demonstrated ability to quickly grasp new scientific domains and apply critical thinking to novel challenges, adapting to evolving project needs.
- 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.
