computational chemist

FullThrottle Labs Pvt Ltd

Position SummaryAs a Computational Materials Discovery Scientist, you will work at the intersection of materials science, computational chemistry, condensed matter physics, quantum computing, and AI/ML. You will contribute to first-principles simulations, molecular and mesoscale modeling, materials informatics pipelines, and hybrid quantum&ndash;classical algorithms for accelerated discovery of materials, catalysts, semiconductors, polymers, and functional systems.This role is ideal for candidates who want to solve real scientific and industrial problems using DFT, MD, multiscale modeling, machine learning, and emerging quantum computing techniques, fully integrated with QpiAI&rsquo;s AI and quantum computing platforms.RequirementsCore Technical Skills*&nbsp;*1. Computational &amp;amp; Quantum Mechanical Methods*&nbsp;*Electronic Structure &amp;amp; Quantum Methods- Density Functional Theory (DFT)&nbsp;- Ab initio Molecular Dynamics (AIMD)- Time-dependent DFT (TDDFT) for excited states- DFT+U for strongly correlated systems- Hybrid functionals&nbsp;- Hartree&ndash;Fock and post-HF methods (MP2, CCSD(T))Molecular &amp;amp; Statistical Simulations- Classical Molecular Dynamics (MD)- Force-field development and validation- Monte Carlo (MC) simulations- Kinetic Monte Carlo (kMC) for surface reactions- Machine Learning Force Fields ( Fairchem, Universal Forcefield, MACE)Multiscale &amp;amp; Mesoscale Modeling- Hierarchical nano &rarr; micro &rarr; meso &rarr; macro modeling- QM&ndash;MM and QM&ndash;continuum coupling- Microkinetic modeling and reaction networks- Phase-field modeling- Free energy methods (umbrella sampling, metadynamics)2. Materials Simulation &amp;amp; Electronic Structure Modeling- Bulk and surface DFT calculations- k-point convergence, basis set testing- Band structure, DOS, PDOS- Phonons and lattice dynamics- Elastic constants, thermal &amp;amp; mechanical properties- Defect formation energies- Phase stability &amp;amp; convex hulls- Slab models and adsorption energies- Reaction pathways using NEB / CI-NEBBenchmarking &amp;amp; Validation- Cross-code benchmarking across:- DFT engines: VASP, Quantum ESPRESSO, CP2K, GPAW, CASTEP, Gaussian, ORCA- MD engines: LAMMPS, GROMACS, NAMD- ML potential3. Materials Informatics &amp;amp; AI/ML- Build ML models for materials &amp;amp; catalyst property prediction:- Fairchem, Universal Forcefield, CGCNN, MEGNet, SchNet, e3nn, NequIP- Transformer &amp;amp; foundation models for materials- Curate datasets from:- Materials Project, OQMD, NOMAD, JARVIS- Develop ML surrogates for:- Energy &amp;amp; force prediction- Bandgap estimation- Thermal &amp;amp; mechanical properties- Catalyst screening &amp;amp; ranking- Integrate ML pipelines with:- DFT / MD workflows- Quantum simulation pipelines4. Simulation Workflow Engineering- Build reproducible, automated workflows in Python for:- High-throughput materials screening- DFT&ndash;MD&ndash;CG-Mesoscale simulation pipelines- Data extraction &amp;amp; post-processing- Develop modular tools for:- Structure parsing (CIF, POSCAR, XYZ, PDB)- Geometry builders &amp;amp; surface generators- Parameters generations&nbsp;- Visualization (band structure, DOS, phonons, trajectories)- Deploy workflows on:- HPC clusters- Cloud platforms (AWS, GCP)- Containerized environments (Docker)5. Research, Collaboration &amp;amp; Documentation- Conduct literature reviews in:- Computational materials- Catalysis- Semiconductors- Alloy and Ceramics- Polymers- Quantum algorithms- Design, execute, and analyze numerical experiments- Prepare:- Technical reports- Internal whitepapers- Presentations and datasets- Collaborate closely with:- Quantum hardware teams- Algorithm developers- AI/ML engineersSpecialization Tracks&nbsp;*&nbsp;*A. DFT &amp;amp; Electronic Structure Specialization- Advanced XC functional selection &amp;amp; benchmarking- Strongly correlated systems (DFT+U, Hubbard models)- Excited-state calculations (TDDFT, GW &ndash; exposure preferred)- Defects, surfaces, and interfaces- Electronic transport &amp;amp; conductivity modelingB. Molecular Dynamics &amp;amp; Classical Simulations- Classical MD simulations (LAMMPS, GROMACS)- Force-field parameterization &amp;amp; validation- Free energy calculations- Reactive force fields (ReaxFF)- ML-accelerated MD workflows- Parameter generation for coarse-grained simulationsC. Catalysis Specialization- Heterogeneous, homogeneous &amp;amp; electro-catalysis- Reaction pathway identification- Transition state searches (NEB, CI-NEB)- Adsorption energies &amp;amp; surface thermodynamics- Microkinetic modeling- Applications:- OER, ORR, HER- Photocatalysis- Single-atom &amp;amp; nanocluster catalystsD. Polymers &amp;amp; Soft Matter Specialization- DFT-based parameter extraction for polymers- Multiscale polymer modeling (DFT, AA, CG)- Dissipative Particle Dynamics (DPD)- Monte Carlo Simulations- Polymer blends, Polymer nanocomposites, surfactants, colloids- Polymerization, degradation, crosslinking, morphology and aging studies- Integration of DFT &rarr; MD &rarr; DPD&rarr;Phase field simulations pipelinesE. Quantum Computing for Materials Simulation- Map materials Hamiltonians to qubits:- Jordan&ndash;Wigner, Bravyi&ndash;Kitaev, parity mappings- Work on quantum algorithms including:- VQE for correlated materials- Subspace Quantum Diagonalization (SQD)- qEOM for excited states- Quantum Phase Estimation- QITE / Quantum Monte Carlo- Analyze:- Qubit requirements- Circuit depth- Noise &amp;amp; error budgets- Design material-specific ans&auml;tze for NISQ devices and simulators*&nbsp;*Software &amp;amp; Programming Skills- DFT Codes: VASP, QE, CP2K, Gaussian, ORCA, CASTEP, ADF- MD Codes: LAMMPS, GROMACS, NAMD, AMBER- Visualization: VMD, VESTA, OVITO, Materials Studio, ASE- Programming: Python (mandatory), Bash- ML: PyTorch, TensorFlow, scikit-learn- Infrastructure: HPC, MPI, Docker, Git, AWS / GCPSoft Skills- Strong analytical and first-principles thinking- Ability to design reproducible scientific workflows- Clear scientific communication- High ownership and curiosity-driven research mindsetEducational Qualifications- PhD (or pursuing PhD for intern role) in:- Chemistry- Materials Science- Chemical Engineering- Physics- Computational Science or related STEM field- Strong foundation in:- Physical chemistry- Quantum mechanics- Statistical mechanics &amp;amp; thermodynamics- Specialization in computational chemistry / materials modeling strongly preferredPreferred Qualifications- Publications or strong computational project portfolio- Experience with HPC &amp;amp; large-scale simulations- Prior work in:- Materials discovery- Catalysis- Semiconductor- Polymer modeling- ML-driven materials science- Exposure to quantum algorithms or hybrid quantum&ndash;classical workflowsJob Type: Full-timePay: ₹1,200,000.00 - ₹1,800,000.00 per yearWork Location: In personSpeak with the employer +91 9008078505

Computational Materials Discovery Scientist

Role OverviewThe company is an AI-driven computational drug discovery platform integrating cheminformatics, structural biology, systems biology, machine learning, quantum computing, and scalable scientific workflows to accelerate the identification of novel therapeutics.We are seeking Senior Computational Drug Discovery Scientists to design, implement, validate, and productionize core scientific workflows for both small molecule and target discovery programs. This role requires deep scientific expertise combined with platform-oriented systems thinking to translate research into production-grade pipelines.Key Responsibilities1. Small Molecule Drug Design Workflows (LBDD/SBDD)- Lead and implement workflows for de novo design, virtual screening, molecular docking, molecular dynamics (MD) simulations, FEP, QSAR/QSPR, and pharmacophore modeling, leveraging open-source packages (AutoDock Vina, GROMACS, LAMMPS, deep-learning accelerated solvers).- Design, validate, and productionize screening pipelines for hit identification, ADMET prediction, and lead optimization.- Conduct Structure-Activity Relationship (SAR) analysis, chemical space exploration, and property optimization using computational methods.- Establish standards for compound library curation and high-quality assay data standardization for model training.2. Target and Systems Biology Discovery- Drive novel target identification and validation using multi-omics data (genomics, proteomics, transcriptomics), network biology, and literature mining.- Perform pathway analysis and deep disease biology interpretation to generate mechanism-level hypotheses for drug programs.- Build scalable, production-ready workflows for biological data integration and quantitative target prioritization.3. Platform Integration and ML/AI Application- Design modular, reproducible computational chemistry and biology workflows.- Collaborate with software teams to productionize and scale pipelines on cloud/HPC.- Integrate deep learning models with model tracking, versioning, and deployment.- Support development and/or integration of agentic workflows into platforms.- Contribute to scientific documentation and intellectual property (IP) generation.Required Technical Skills- Strong expertise in at least one core area of computational drug discovery:- Ligand-Based Drug Design (LBDD) and/or Structure-Based Drug Design (SBDD)- Computational Structural Biology (MD, FEP, docking, with proficiency in tools like GROMACS, AMBER, NAMD, and Desmond)- Computational Systems Biology / Target Discovery- Hands-on experience with forcefield-based simulations.- Direct exposure to implementing and utilizing deep learning in drug discovery, including generative models.- Advanced proficiency in Python programming (RDKit, NumPy, PyTorch)- Proven experience building and optimizing scalable computational scientific pipelines.- Solid understanding of the end-to-end small molecule drug discovery decision process.- Strong knowledge of best practices in benchmarking, reproducibility, and rigorous scientific validation.Preferred Skills- Track record of contributions to research publications, patent applications, or invention disclosures.Educational Qualifications- PhD in one of the following (mandatory):- Computational Chemistry- Cheminformatics- Computational Biology- Drug Discovery- Systems Biology- Related quantitative life sciences disciplineExperience Requirements- 2&ndash;5 years of relevant post-PhD experience in computational drug discovery/design and platform development or related fields.- Demonstrated experience building end-to-end, high-throughput computational screening and analysis workflows.- Experience working with complex, real-world biological and chemical datasets in a pharmaceutical or biotech context.- Proven exposure to interdisciplinary collaboration.Job Type: Full-timePay: ₹1,200,000.00 - ₹1,500,000.00 per yearWork Location: In personSpeak with the employer +91 9008078505

Senior Computational Drug Discovery Scientist

ExxonMobil India Careers

<div>
 
 About Us
 
 
 At ExxonMobil, our vision is to lead in energy innovations that advance modern living and a net-zero future. As one of the world&rsquo;s largest publicly traded energy and chemical companies, we are powered by a unique and diverse workforce fueled by the pride in what we do and what we stand for.
 
 
 The success of our Upstream, Product Solutions and Low Carbon Solutions businesses is the result of the talent, curiosity and drive of our people. They bring solutions every day to optimize our strategy in energy, chemicals, lubricants and lower-emissions technologies.
 
 
 We invite you to bring your ideas to ExxonMobil to help create sustainable solutions that improve quality of life and meet society&rsquo;s evolving needs. Learn more about
 
 our What and our Why
 
 and how we can work
 
 together
 
 .
 
 
 
 ExxonMobil&rsquo;s affiliates in India
 
 
 
 ExxonMobil&rsquo;s affiliates have offices in India in Bengaluru, Mumbai and the National Capital Region.
 
 
 ExxonMobil&rsquo;s affiliates in India supporting the Product Solutions business engage in the marketing, sales and distribution of performance as well as specialty products across chemicals and lubricants businesses. The India planning teams are also embedded with global business units for business planning and analytics.
 
 
 ExxonMobil&rsquo;s LNG affiliate in India supporting the upstream business provides consultant services for other ExxonMobil upstream affiliates and conducts LNG market-development activities.
 
 
 The Global Business Center - Technology Center provides a range of technical and business support services for ExxonMobil&rsquo;s operations around the globe.
 
 
 ExxonMobil strives to make a positive contribution to the communities where we operate and its affiliates support a range of education, health and community-building programs in India. Read more about our Corporate Responsibility Framework.
 
 
 To know more about ExxonMobil in India, visit ExxonMobil India and the Energy Factor India.
 
 
 
 What Role You Will Play In Our Team
 
 
 We are seeking candidates with a strong research record and expertise in Computational Materials Science and Engineering or related fields. The role focuses on designing material structures, predicting properties and behaviors, and applying advanced modeling techniques to accelerate materials discovery and development, particularly in polymers, complex fluids, structural and functional materials.
 
 
 You will work across a wide range of applications where key material properties, such as mechanical performance, rheology, thermodynamics, and stability, are critical to success. This position requires strong expertise in a variety of computational techniques and broad experience in modeling and simulating complex materials (e.g., polymers) under real-world conditions and uncovering structure&ndash;process&ndash;property&ndash;performance relationships.
 
 
 
 What You Will Do
 
 
 <ul>
 <li>
 Apply advanced modeling to accelerate materials discovery and development and enable in-silico materials design
 </li>
 <li>
 Investigate physical processes and mechanisms across multiple length and time scales.
 </li>
 <li>
 Collaborate closely with experimentalists and other modeling experts to validate and improve models.
 </li>
 <li>
 Develop and deploy computational models that address business needs and enhance research workflows.
 
 
 </li>
 </ul>
 
 Skills and Qualifications:
 
 
 
 <ul>
 <li>
 Ph.D. in Materials Science and Engineering, Chemical Engineering, Chemistry, Physics, Computational Science, or related fields.
 </li>
 <li>
 Minimum 3 years of research experience in materials modeling (including Ph.D. research).
 </li>
 <li>
 Proven experience in modeling and simulating behavior of complex materials such as semicrystalline polymers, hydrocarbons, soft matter, complex fluids, and composites.
 </li>
 <li>
 Proficiency in atomistic simulations, Density Functional Theory, molecular dynamics, Monte Carlo, coarse-grained methods, and/or finite element analysis.
 </li>
 <li>
 Expertise in multiscale and multi-physics modeling, including techniques from ab-initio to continuum methods across a broad range of time and length scales.
 </li>
 <li>
 Experience with hybrid modeling and integrating physics-based and data-driven methods (e.g., machine learning)
 </li>
 <li>
 Experience with forcefield development and MLIPs (Machine Learning Interatomic Potentials).
 </li>
 <li>
 Experience with both CPU and GPU high-performance computing.
 </li>
 <li>
 Strong programming skills (Python, C++, scripting for automation).
 </li>
 <li>
 Excellent communication and collaboration skills across multidisciplinary teams.
 
 
 </li>
 </ul>
 
 Preferred Experiences:
 
 
 
 <ul>
 <li>
 Polymer physics, soft matter physics, fluid mechanics
 </li>
 <li>
 Thermodynamics, statistical mechanics, interface science, and kinetic modeling
 </li>
 <li>
 Machine learning, statistical modeling, materials informatics
 </li>
 <li>
 Experience in energy and sustainability-related materials
 
 
 </li>
 </ul>
 
 Your Benefits
 
 
 An ExxonMobil career is one designed to last. Our commitment to you runs deep: our employees grow personally and professionally, with benefits built on our core categories of health, security, finance and life. We offer you:
 
 
 <ul>
 <li>
 Competitive compensation
 </li>
 <li>
 Medical plans, maternity leave and benefits, life, accidental death and dismemberment benefits
 </li>
 <li>
 Retirement benefits
 </li>
 <li>
 Global networking &amp; cross-functional opportunities
 </li>
 <li>
 Annual vacations &amp; holidays
 </li>
 <li>
 Day care assistance program
 </li>
 <li>
 Training and development program
 </li>
 <li>
 Tuition assistance program
 </li>
 <li>
 Workplace flexibility policy
 </li>
 <li>
 Relocation program
 </li>
 <li>
 Transportation facility
 
 
 </li>
 </ul>
 Please note benefits may change from time to time without notice, subject to applicable laws. The benefits programs are based on the Company&rsquo;s eligibility guidelines.
 
 
 
 Stay Connected With Us
 
 
 
 <ul>
 <li>
 Learn more about ExxonMobil in India, visit ExxonMobil India and Energy Factor India.
 </li>
 <li>
 Follow us on LinkedIn and Instagram
 </li>
 <li>
 Like us on Facebook
 </li>
 <li>
 Subscribe our channel at YouTube
 
 
 </li>
 </ul>
 
 EEO Statement
 
 
 ExxonMobil is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin or disability status.
 
 
 
 Business solicitation and recruiting scams
 
 
 ExxonMobil does not use recruiting or placement agencies that charge candidates an advance fee of any kind (e.g., placement fees, immigration processing fees, etc.). Follow the LINK to understand more about recruitment scams in the name of ExxonMobil.
 
 
 Nothing herein is intended to override the corporate separateness of local entities. Working relationships discussed herein do not necessarily represent a reporting connection, but may reflect a functional guidance, stewardship, or service relationship.
 
 
 Exxon Mobil Corporation has numerous affiliates, many with names that include ExxonMobil, Exxon, Esso and Mobil. For convenience and simplicity, those terms and terms like corporation, company, our, we and its are sometimes used as abbreviated references to specific affiliates or affiliate groups. Abbreviated references describing global or regional operational organizations and global or regional business lines are also sometimes used for convenience and simplicity. Similarly, ExxonMobil has business relationships with thousands of customers, suppliers, governments, and others. For convenience and simplicity, words like venture, joint venture, partnership, co-venturer, and partner are used to indicate business relationships involving common activities and interests, and those words may not indicate precise legal relationships.
</div>

Computational Materials Scientist

ExxonMobil

<div>About us 
At ExxonMobil, our vision is to lead in energy innovations that advance modern living and a net-zero future. As one of the world&rsquo;s largest publicly traded energy and chemical companies, we are powered by a unique and diverse workforce fueled by the pride in what we do and what we stand for. 
The success of our Upstream, Product Solutions and Low Carbon Solutions businesses is the result of the talent, curiosity and drive of our people. They bring solutions every day to optimize our strategy in energy, chemicals, lubricants and lower-emissions technologies. 
We invite you to bring your ideas to ExxonMobil to help create sustainable solutions that improve quality of life and meet society&rsquo;s evolving needs. Learn more about our What and our Why and how we can work together.<div><div><div><h2 class="jobSectionHeader">
ExxonMobil&rsquo;s affiliates in India</h2></div><div>
ExxonMobil&rsquo;s affiliates have offices in India in Bengaluru, Mumbai and the National Capital Region. 
ExxonMobil&rsquo;s affiliates in India supporting the Product Solutions business engage in the marketing, sales and distribution of performance as well as specialty products across chemicals and lubricants businesses. The India planning teams are also embedded with global business units for business planning and analytics. 
ExxonMobil&rsquo;s LNG affiliate in India supporting the upstream business provides consultant services for other ExxonMobil upstream affiliates and conducts LNG market-development activities. 
The Global Business Center - Technology Center provides a range of technical and business support services for ExxonMobil&rsquo;s operations around the globe. 
ExxonMobil strives to make a positive contribution to the communities where we operate and its affiliates support a range of education, health and community-building programs in India. Read more about our Corporate Responsibility Framework. 
To know more about ExxonMobil in India, visit ExxonMobil India and the Energy Factor India.</div></div><div><div><h2 class="jobSectionHeader">
What role you will play in our team</h2></div><div>
We are seeking candidates with a strong research record and expertise in Computational Materials Science and Engineering or related fields. The role focuses on designing material structures, predicting properties and behaviors, and applying advanced modeling techniques to accelerate materials discovery and development, particularly in polymers, complex fluids, structural and functional materials. 
You will work across a wide range of applications where key material properties, such as mechanical performance, rheology, thermodynamics, and stability, are critical to success. This position requires strong expertise in a variety of computational techniques and broad experience in modeling and simulating complex materials (e.g., polymers) under real-world conditions and uncovering structure&ndash;process&ndash;property&ndash;performance relationships.</div></div><div><div><h2 class="jobSectionHeader">
What you will do</h2></div><div> 
<ul><li>
Apply advanced modeling to accelerate materials discovery and development and enable in-silico materials design</li><li>
Investigate physical processes and mechanisms across multiple length and time scales.</li><li>
Collaborate closely with experimentalists and other modeling experts to validate and improve models.</li><li>
Develop and deploy computational models that address business needs and enhance research workflows.</li></ul></div></div><div><div><h2 class="jobSectionHeader">
Skills and Qualifications:</h2></div><div><ul><li>
Ph.D. in Materials Science and Engineering, Chemical Engineering, Chemistry, Physics, Computational Science, or related fields.</li><li>
Minimum 3 years of research experience in materials modeling (including Ph.D. research).</li><li>
Proven experience in modeling and simulating behavior of complex materials such as semicrystalline polymers, hydrocarbons, soft matter, complex fluids, and composites.</li><li>
Proficiency in atomistic simulations, Density Functional Theory, molecular dynamics, Monte Carlo, coarse-grained methods, and/or finite element analysis.</li><li>
Expertise in multiscale and multi-physics modeling, including techniques from ab-initio to continuum methods across a broad range of time and length scales.</li><li>
Experience with hybrid modeling and integrating physics-based and data-driven methods (e.g., machine learning)</li><li>
Experience with forcefield development and MLIPs (Machine Learning Interatomic Potentials).</li><li>
Experience with both CPU and GPU high-performance computing.</li><li>
Strong programming skills (Python, C++, scripting for automation).</li><li>
Excellent communication and collaboration skills across multidisciplinary teams.</li></ul></div></div><div><div><h2 class="jobSectionHeader">
Preferred Experiences:</h2></div><div><ul><li>
Polymer physics, soft matter physics, fluid mechanics</li><li>
Thermodynamics, statistical mechanics, interface science, and kinetic modeling</li><li>
Machine learning, statistical modeling, materials informatics</li><li>
Experience in energy and sustainability-related materials</li></ul></div></div><div><div><h2 class="jobSectionHeader">
Your Benefits</h2></div><div> 
An ExxonMobil career is one designed to last. Our commitment to you runs deep: our employees grow personally and professionally, with benefits built on our core categories of health, security, finance and life. We offer you:<ul><li>
Competitive compensation</li><li>
Medical plans, maternity leave and benefits, life, accidental death and dismemberment benefits</li><li>
Retirement benefits</li><li>
Global networking &amp; cross-functional opportunities</li><li>
Annual vacations &amp; holidays</li><li>
Day care assistance program</li><li>
Training and development program</li><li>
Tuition assistance program</li><li>
Workplace flexibility policy</li><li>
Relocation program</li><li>
Transportation facility</li></ul> 
Please note benefits may change from time to time without notice, subject to applicable laws. The benefits programs are based on the Company&rsquo;s eligibility guidelines.</div></div><div><div><h2 class="jobSectionHeader">
Stay Connected With Us</h2></div><div> 
<ul><li>
Learn more about ExxonMobil in India, visit ExxonMobil India and Energy Factor India.</li><li>
Follow us on LinkedIn and Instagram</li><li>
Like us on Facebook</li><li>
Subscribe our channel at YouTube</li></ul> 
EEO Statement 
ExxonMobil is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin or disability status. 
Business solicitation and recruiting scams 
ExxonMobil does not use recruiting or placement agencies that charge candidates an advance fee of any kind (e.g., placement fees, immigration processing fees, etc.). Follow the LINK to understand more about recruitment scams in the name of ExxonMobil.</div></div></div> 
Nothing herein is intended to override the corporate separateness of local entities. Working relationships discussed herein do not necessarily represent a reporting connection, but may reflect a functional guidance, stewardship, or service relationship. 
Exxon Mobil Corporation has numerous affiliates, many with names that include ExxonMobil, Exxon, Esso and Mobil. For convenience and simplicity, those terms and terms like corporation, company, our, we and its are sometimes used as abbreviated references to specific affiliates or affiliate groups. Abbreviated references describing global or regional operational organizations and global or regional business lines are also sometimes used for convenience and simplicity. Similarly, ExxonMobil has business relationships with thousands of customers, suppliers, governments, and others. For convenience and simplicity, words like venture, joint venture, partnership, co-venturer, and partner are used to indicate business relationships involving common activities and interests, and those words may not indicate precise legal relationships.</div>

Biogen

<div>Scientist, Machine Learning, Molecular Design
About This Role
The Computational Molecular Science team at Biogen is searching for a scientist interested in machine learning applications and transformative artificial intelligence algorithms to accelerate and improve the established small molecule design cycle that consists of idea generation, evaluation, and synthesis. This is a unique opportunity to join a cross-functional team working at the intersection of computational, chemical, and biological sciences and have direct access to a wealth of structured and unstructured data across the Biogen research organization to make a massive impact on redefining the early drug-discovery platform.
What You&rsquo;ll Do
<ul><li>Build and deploy ML-driven molecular design workflows that combine deep generative models and deep reinforcement learning to propose and prioritize small molecules under multi-parameter objectives (potency, ADMET, novelty, synthesizability).
</li>Develop and maintain predictive models and molecular representations (e.g., GNNs/Transformers, 2D/3D features) and integrate them into iterative &ldquo;generate score<li> learn&rdquo; design loops.
</li><li>Collaborate with Computational Chemistry and cross-functional Drug Discovery teams to translate project needs into robust, reproducible tools and deliver measurable impact on small-molecule programs.
</li><li>Publish and present methodological and applied work internally and externally.
</li></ul>The successful candidate will be a creative and highly motivated scientist with demonstrated expertise in the field of machine learning and cheminformatics. You will be expected to stay current with the scientific literature and apply the latest advances in computational methods to address drug discovery challenges. As a key contributor to the molecule informatics group, thinking independently to solve complex problems is an important aspect of this position.
Required Skills
<ul><li>Ph.D. in Computer Science (or related field) with strong fundamentals in machine learning, deep learning, and optimization.
</li><li>1+ years of postdoctoral experience with demonstrated ability to lead research projects independently and deliver high-quality results.
</li><li>Proven ability to work effectively in a multidisciplinary environment.
</li><li>Strong track record of publications and/or scientific presentations demonstrating impact and scientific rigor.
</li><li>Excellent oral and written communication skills, including the ability to explain technical work to both technical and non-technical audiences.
</li></ul>Preferred Skills
<ul><li>Strong hands-on experience developing and training deep learning models end-to-end (data pipelines, model design, training loops, debugging, and evaluation) using PyTorch or TensorFlow.
</li><li>Proven experience with modern deep generative models for molecular design (e.g., Transformer, GAN; diffusion/graph models are a plus)
</li><li>Experience applying deep reinforcement learning and/or multi-objective optimization to molecular generation and prioritization (e.g., reward design, constraint handling, Pareto trade-offs).
</li><li>Solid understanding of deep learning best practices (regularization, hyperparameter tuning, representation learning, uncertainty estimation, and generalization under data shift).
</li>Strong Python skills and practical experience with the ML ecosystem; cheminformatics experience is a plus. 
<li>
</li></ul> 
Job Level: Professional 
 
Additional Information
The base compensation range for this role is: $117,000.00-$152,000.00 
<div> 
Base salary offered is determined through an analytical approach utilizing a combination of factors including, but not limited to, relevant skills &amp; experience, job location, and internal equity.
Regular employees are eligible to receive both short term and long-term incentives, including cash bonus and equity incentive opportunities, designed to reward recent achievements and recognize your future potential based on individual, business unit and company performance.
In addition to compensation, Biogen offers a full and highly competitive range of benefits designed to support our employees&rsquo; and their families physical, financial, emotional, and social well-being ; including, but not limited to:
<ul><li>Medical, Dental, Vision, &amp; Life insurances
</li><li>Fitness &amp; Wellness programs including a fitness reimbursement
</li><li>Short- and Long-Term Disability insurance
</li><li>A minimum of 15 days of paid vacation and an additional end-of-year shutdown time off (Dec 26-Dec 31)
</li><li>Up to 12 company paid holidays + 3 paid days off for Personal Significance
</li><li>80 hours of sick time per calendar year
</li><li>Paid Maternity and Parental Leave benefit
</li><li>401(k) program participation with company matched contributions
</li><li>Employee stock purchase plan
</li><li>Tuition reimbursement of up to $10,000 per calendar year
</li><li>Employee Resource Groups participation
</li></ul></div><div>Why Biogen?
We are a global team with a commitment to excellence, and a pioneering spirit. As a mid-sized biotechnology company, we provide the stability and resources of a well-established business while fostering an environment where individual contributions make a significant impact. Our team encompasses some of the most talented and passionate achievers who have unparalleled opportunities for learning, growth, and expanding their skills. Above all, we work together to deliver life-changing medicines, with every role playing a vital part in our mission. Caring Deeply. Achieving Excellence. Changing Lives.
At Biogen, we are committed to building on our culture of inclusion and belonging that reflects the communities where we operate and the patients we serve. We know that diverse backgrounds, cultures, and perspectives make us a stronger and more innovative company, and we are focused on building teams where every employee feels empowered and inspired. Read on to learn more about our DE&amp;I efforts.
All qualified applicants will receive consideration for employment without regard to sex, gender identity or expression, sexual orientation, marital status, race, color, national origin, ancestry, ethnicity, religion, age, veteran status, disability, genetic information or any other basis protected by federal, state or local law. Biogen is an E-Verify Employer in the United States.</div></div>

Scientist, Machine Learning, Molecular Design

DataAnnotation

<div>
 We are looking for a Research Scientist (Chemistry) to join our team to train AI models. You will measure the progress of these AI chatbots, evaluate their logic, and solve problems to improve the quality of each model.
 
 
 In this role you will need to hold an expert level understanding of chemistry. Other related fields include, but are not limited to: Research and Development Chemist, Formulation Scientist, Development Chemist, Analytical Chemist, Chemical Engineer, Medicinal Chemist, Biochemist, Process Development Chemist.
 
 
 
 Benefits
 
 
 
 <ul>
 <li>
 This is a full-time or part-time REMOTE position
 </li>
 <li>
 You&rsquo;ll be able to choose which projects you want to work on
 </li>
 <li>
 You can work on your own schedule
 </li>
 <li>
 Projects are paid hourly starting at $40+ USD per hour, with bonuses on high-quality and high-volume work
 
 
 </li>
 </ul>
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Give AI chatbots complex chemistry questions and evaluate their outputs
 </li>
 <li>
 Evaluate the quality produced by AI models for correctness and performance
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Fluency in English (native or bilingual level)
 </li>
 <li>
 Detail-oriented
 </li>
 <li>
 Solid knowledge of general, organic, and physical chemistry concepts
 </li>
 <li>
 A current, in progress, or completed Masters and/or PhD is preferred but not required
 
 
 </li>
 </ul>
 
 Notes
 
 
 
 Payment is made via PayPal. We will never ask for any money from you. PayPal will handle any currency conversions from USD. Only applicants in the United States will be considered for this role. This is an independent contract position.
 
 
 #chem
</div>

Research Scientist (Chemistry)

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214 computational chemist jobs Near Me

Computational Materials Discovery Scientist

Senior Computational Drug Discovery Scientist

Computational Materials Scientist

Computational Materials Scientist

Scientist, Machine Learning, Molecular Design

Research Scientist (Chemistry)

Research Scientist (Chemistry)