computational scientist

ExxonMobil India Careers

<div>
 <strong>
  About Us
  <br/>
 </strong>
 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.
 <br/>
 <br/>
 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.
 <br/>
 <br/>
 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
 <strong>
  our What and our Why
 </strong>
 and how we can work
 <strong>
  together
 </strong>
 .
 <br/>
 <br/>
 <strong>
  ExxonMobil&rsquo;s affiliates in India
  <br/>
  <br/>
 </strong>
 ExxonMobil&rsquo;s affiliates have offices in India in Bengaluru, Mumbai and the National Capital Region.
 <br/>
 <br/>
 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.
 <br/>
 <br/>
 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.
 <br/>
 <br/>
 The Global Business Center - Technology Center provides a range of technical and business support services for ExxonMobil&rsquo;s operations around the globe.
 <br/>
 <br/>
 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.
 <br/>
 <br/>
 To know more about ExxonMobil in India, visit ExxonMobil India and the Energy Factor India.
 <br/>
 <br/>
 <strong>
  What Role You Will Play In Our Team
  <br/>
 </strong>
 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.
 <br/>
 <br/>
 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.
 <br/>
 <br/>
 <strong>
  What You Will Do
  <br/>
 </strong>
 <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.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Skills and Qualifications:
  <br/>
  <br/>
 </strong>
 <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.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Preferred Experiences:
  <br/>
  <br/>
 </strong>
 <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
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Your Benefits
  <br/>
 </strong>
 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:
 <br/>
 <br/>
 <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
   <br/>
   <br/>
  </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.
 <br/>
 <br/>
 <strong>
  Stay Connected With Us
  <br/>
  <br/>
 </strong>
 <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
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  EEO Statement
  <br/>
 </strong>
 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.
 <br/>
 <br/>
 <strong>
  Business solicitation and recruiting scams
  <br/>
 </strong>
 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.
 <br/>
 <br/>
 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.
 <br/>
 <br/>
 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

<p></p><div><p><b>About us</b></p><p></p><p><br>
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.</p><p></p><p><br>
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.</p><p></p><p><br>
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 <b>our What and our Why</b> and how we can<b> </b>work<b> together</b>.</p><div><div><div><h2 class="jobSectionHeader"><b>
ExxonMobil&rsquo;s affiliates in India</b></h2></div><div><p>
ExxonMobil&rsquo;s affiliates have offices in India in Bengaluru, Mumbai and the National Capital Region.</p><p></p><p><br>
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.</p><p></p><p><br>
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.</p><p><br>
The Global Business Center - Technology Center provides a range of technical and business support services for ExxonMobil&rsquo;s operations around the globe.</p><p><br>
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.</p><p><br>
To know more about ExxonMobil in India, visit ExxonMobil India and the Energy Factor India.</p></div></div><div><div><h2 class="jobSectionHeader"><b>
What role you will play in our team</b></h2></div><div><p>
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.</p><p><br>
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.</p></div></div><div><div><h2 class="jobSectionHeader"><b>
What you will do</b></h2></div><p></p><div><br>
<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"><b>
Skills and Qualifications:</b></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"><b>
Preferred Experiences:</b></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"><b>
Your Benefits</b></h2></div><p></p><div><p><br>
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:</p><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><p></p><p><br>
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.</p></div></div><div><div><h2 class="jobSectionHeader"><b>
Stay Connected With Us</b></h2></div><p></p><div><br>
<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><p></p><p><b><br>
EEO Statement</b></p><p></p><p><br>
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.</p><p></p><p><b><br>
Business solicitation and recruiting scams</b></p><p></p><p><br>
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.</p></div></div></div><p></p><p><br>
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.</p><p></p><p><br>
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.</p></div>

St. Jude Children's Research Hospital

<div><b>Job Description</b><br>
<br>
We are seeking a highly motivated computational biologist to join our lab at St. Jude Children's Research Hospital to lead genomic and single-cell analysis for projects focused on bacterial heterogeneity, microbiome interactions, antibiotic response, and genome architecture.<br>
Our group develops and applies cutting-edge bacterial single-cell RNA-seq platforms, long-read sequencing, and functional genomics to uncover how pathogens adapt in hosts and respond to drugs. This position is ideal for someone who wants to drive analysis, shape biological stories, and grow into a senior computational scientist in a hybrid experimental-computational environment.<br>
<br>
<b>What You Will Do
</b><br>
<br>
<ul><li>Lead analysis of microbiome datasets (metagenomics, strain-level profiling, 16S).</li></ul><br>
<ul><li>Analyze bacterial scRNA-seq and long-read transcriptomic data.</li></ul><br>
<ul><li>Detect and interpret structural variation from Nanopore/PacBio sequencing.</li></ul><br>
<ul><li>Build scalable, reproducible pipelines for large genome collections and public databases.</li></ul><br>
<ul><li>Collaborate closely with experimental scientists to frame hypotheses and interpret results.</li></ul><br>
<ul><li>Co-author high-impact manuscripts and grant proposals.</li></ul><br>
<ul><li>Mentor trainees developing computational skills.</li></ul><br>
<b>
We Are Looking For Someone Who
</b><br>
<br>
<ul><li>Has a PhD in computational biology, genomics, bioinformatics, microbiology, or a related field.</li></ul><br>
<ul><li>Is fluent in Python/R and Unix-based workflows.</li></ul><br>
<ul><li>Has experience with microbial genomics, metagenomics, or long-read sequencing.</li></ul><br>
<ul><li>Can design analyses independently and anticipate reviewer concerns.</li></ul><br>
<ul><li>Enjoys shaping projects scientifically-not just executing tasks.</li></ul><br>
<b>
Especially Excited If You Have
</b><br>
<br>
<ul><li>Experience with RNA-seq.</li></ul><br>
<ul><li>Structural-variant detection or genome architecture analysis.</li></ul><br>
<ul><li>Workflow frameworks (Snakemake, Nextflow, WDL).</li></ul><br>
<ul><li>Large-scale comparative genomics.</li></ul><br>
This is a leadership-track computational role for someone who wants to define a research program inside a fast-moving, biology-driven lab.<br>
<br>
St. Jude is an Equal Opportunity Employer
<br>
<br>
<b>No Search Firms</b>
<br>
<br>
St. Jude Children's Research Hospital does not accept unsolicited assistance from search firms for employment opportunities. Please do not call or email. All resumes submitted by search firms to any employee or other representative at St. Jude via email, the internet or in any form and/or method without a valid written search agreement in place and approved by HR will result in no fee being paid in the event the candidate is hired by St. Jude.</div>

Postdoctoral Research Associate -Microbiome, Bacterial Genomics, and Single-Cell Genomics

AgSource

<div><div><div><div>JOB DESCRIPTION<br>
URUS is seeking a Computational Biologist to join our Innovation group as part of the team focused on Genetic Advancement and Trait Discovery. This role is suited for a creative and career motivated individual who brings strong expertise across multiple disciplines of genomics, bioinformatics, and systems biology. The successful candidate will lead the integration, analyses and interpretation of genomic and multi-omics data to identify biological pathways, DNA sequence motifs or genomic variation for rationale design of genetic traits to express phenotypes that significantly improve fertility, protein quality, health or well-being across cattle breeding systems.<br>
</div></div><div></div><div><div>Acceligen &reg;, as part of the URUS group of brands, is the global leader for deployment of gene-edited traits in cattle. Acceligen has more than a decade of proven commercial expertise in trait deployment through new breeding technologies and advanced reproductive technologies. Acceligen works within a collaborative environment that includes URUS Digital, PEAK Genetics, Trans Ova Genetics, Leachman Cattle CO., and VAS with a common goal to breed &ldquo;Better Cows for a Better World&rdquo;. The incumbent will report to the Chief Science Officer of Acceligen , who leads the Genetic Advancement and Trait Discovery team as part of the Innovation group at URUS. This position will be based in Madison, WI or New Brighton, MN.<br>
</div></div><div></div><div><div><b>RESPONSIBILITIES<br>
</b></div></div><p></p><div><div>The main objectives of our Innovation team are to better understand genomics and genetics at the molecular level and apply these findings to accelerate genetic improvement and reproductive efficiencies of select proprietary lineages of dairy and beef cattle.<br>
</div></div><div></div><div><div>The Computational Biologists' goals are to deliver tools and knowledge that facilitate commercial implementation for advancing these goals in the URUS breeding program. The complex nature of the research requires a scientist with a blend of strong biology fundamentals and advanced tech skills (Python/R, ML, stats, databases, high-performance computing) to analyze large biological datasets, model complex systems, and develop predictive tools, alongside possessing creative analytical and problem-solving abilities and interdisciplinary communication skills to bridge biology and computer science for breakthroughs of economic importance to cattle genetics.<br>
</div></div><div></div><div><div><b>PROFESSIONAL QUALIFICATIONS AND EXPERIENCE<br>
</b></div></div><p></p><div><ul><li><div>Ph.D. in Computational Biology, Systems Biology, Genome Science, or a related field .
</div></li><li><div>Biology: Deep understanding of genetics, molecular biology, biochemistry, cellular functions, and organismal systems.
</div></li><li><div>Mathematics &amp; Statistics: Expertise in probability, statistical modeling, and algorithm design.
</div></li><li><div>Computer Science: Principles of programming, data structures, algorithms, high-performance computing (HPC), and database management.
</div></li><li><div>Bioinformatics: Knowledge of specific tools, databases, and analysis methods for genomic/proteomic data.
</div></li><li><div>Livestock Genetics and Genomics: Knowledge and experience in working with genomic and genetic data from food animals is preferred.
</div></li><li><div>Programming: Proficiency in languages like Python (with libraries like Pandas, NumPy, scikit-learn) and R. E xperience managing bioinformatics pipelines in Unix/Linux environments.
</div></li><li><div>Data Analysis &amp; Machine Learning: Strong skills in data mining, machine learning (deep learning, pattern recognition), and biostatistics. Proficient in genome-wide association studies (GWAS) and fine-mapping methods to identify causal variants and regulatory regions. Proven experience in identifying causal variants is preferred.
</div></li><li><div>Data Handling: Ability to manage, integrate, analyze, and visualize large, complex datasets (e.g., Next- Gen Sequencing data and other Omics datasets). Knowledge of Snakemake , Microsoft Azure and Azure Databricks is preferred.
</div></li><li><div>Modeling &amp; Simulation: Experience with mathematical modeling of biological processes and molecular dynamics.
</div></li><li><div>Problem-Solving: Excellent analytical thinking to translate biological questions into computational problems (e.g. demonstrated skill to integrate multi-omics datasets to identify target genes or regulatory motifs/mechanisms within the expressed genome that link genotype to phenotype).
</div></li><li><div>Communication &amp; Collaboration: Required communication skills are fluency in English. Ability to explain complex technical findings to both technical and non-technical audiences. Includes working and communicating within interdisciplinary teams (e.g., molecular and quantitative geneticists, data scientists, and reproductive biologists). Incumbent is solely responsible for analyzing, interpreting, and reporting research data. Results, in the form of manuscripts, reports, and presentations at scientific meetings, are considered authoritative and technically accurate.
</div></li><li><div>Research Acumen: Skill in formulating hypotheses, finding relevant data, and designing computational experiments.
</div></li><li><div>Adaptability: Eagerness to learn new methods and tools to tackle evolving biological challenges.
</div></li><li><div>Attention to Detail: Precision in coding, data interpretation, and validation.
</div></li><li><div>Strategic Planning for Innovation:
</div></li><li><div>Incumbent is responsible for planning specific research approaches and designing experimental schemes to achieve research objectives.
</div></li><li><div>Contribute to long-term research planning and innovation strategies, which include active participation in team and cross-functional meetings.
</div></li><li><div>Originality and creativity are required to integrate appropriate company resources, methodologies , technologies into a cohesive set of analyses that successfully characterize genome structure and function.
</div></li><li><div>Originality and creativity are also required to integrate complex datasets from separate functional and structural genome studies into a federated database that channel subsequent studies towards elucidating how alterations in complex biological processes affect phenotypic expression.</div></li></ul></div></div></div>

Computational Biologist

Biogen

<div><p><b>Scientist, Machine Learning, Molecular Design
</b></p><p></p><p><b>About This Role
</b></p><p></p><p>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.
</p><p></p><p><b>What You&rsquo;ll Do
</b></p><p></p><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><p></p><p>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.
</p><p></p><p><b>Required Skills
</b></p><p></p><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><p></p><p><b>Preferred Skills
</b></p><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.<br>
<li>
</li></ul><p></p><br>
Job Level: Professional<br>
<p><br>
<b>Additional Information
</b></p><p></p>The base compensation range for this role is: $117,000.00-$152,000.00<br>
<div><p><br>
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.
</p><p></p><p>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.
</p><p></p><p>In addition to compensation, Biogen offers a full and highly competitive range of benefits designed to support our employees&rsquo; and their families <i>physical, financial, emotional, </i>and <i>social well-being </i>; including, but not limited to:
</p><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><p></p><div><p><b>Why Biogen?
</b></p><p>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.
</p><p></p><p>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.
</p><p></p><p>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.</p></div></div>

Scientist, Machine Learning, Molecular Design

University of California Los Angeles

<div>Job #JPF10884
<ul><li>Biomathematics / David Geffen School Of Medicin / UCLA</li></ul></div>
<br><div><p>POSITION OVERVIEW</p>
<b>Position title:</b> Assistant Project Scientist
<div><b>Salary range:</b> $76,700-$89,000
</div><div><p>APPLICATION WINDOW</p><b>
</b></div><div><p><b>Open date: </b>March 2, 2026
</p></div><div><p><b>Next review date:</b> Wednesday, Apr 1, 2026 at 11:59pm (Pacific Time)<br>
Apply by this date to ensure full consideration by the committee.
</p></div><div><p><b>Final date: </b>Wednesday, Apr 1, 2026 at 11:59pm (Pacific Time)<br>
Applications will continue to be accepted until this date.
</p></div><p>POSITION DESCRIPTION</p>
<div><div><p>Assistant Project Scientist to work in Department of Computational Medicine. Individual will use computational methods to develop next-generation pandemic response tools. Ph.D. degree in mathematics, computer science, genomics, biomathematics, or related field required.</p>
</div></div>
<p>QUALIFICATIONS</p>
<div><b>Basic qualifications</b>
<div><p>Ph.D. degree in mathematics, computer science, genomics, biomathematics, or related field required.</p>
</div>
</div><p>APPLICATION REQUIREMENTS</p>
<div><div><b>Document requirements</b>
<ul><li><div><p>Curriculum Vitae - Your most recently updated C.V.
</p></div></li><li><div><p>Cover Letter</p>
</div></li><li><div><p>
Statement of Research</p>
</div></li><li><div><p>
Reference check authorization release form - Complete and upload the reference check authorization release form
</p></div></li><li><div><p>UCLA Mission Statement - As the nation's premier public research university, UC's mission is the creation, dissemination, preservation and application of knowledge for the betterment of our global society. We have a particular responsibility to the people of California which we express in the excellence of the education we provide, the impact of the research we do, the comprehensive, life-saving medical services we provide, and the public service mission we are devoted to. The University of California promotes the social mobility of its students, equips them with the tools and experience that furthers their ambitions, and regards their accomplishments across the life span as evidence of the profoundly positive impact of higher education.
</p><p>The UCLA campus has expressed these goals in its strategic plan as follows:
</p><p>Deepen our engagement with Los Angeles
<br>
Expand our reach as a global university
<br>
Enhance our research and creative activities
<br>
Elevate how we teach
<br>
Become a more effective institution
</p><p><b>Prompt for candidates for recruitment:</b>
</p><p>Reflecting on your personal and professional experiences, highlight your past contributions and future commitments to advancing UCLA's mission as embodied in the 2023-28 strategic plan. These accomplishments and ambitions may be discussed in the context of describing your teaching, scholarship, and service
</p></div></li><li><div><p>Statement of Teaching (Optional)</p>
</div></li></ul>
</div><div><div><b>Reference requirements</b></div><ul><li>
3-5 required (contact information only)</li></ul><div><p>
Request contact information for 3 references</p>
</div></div>
<b>Apply link:</b> https://recruit.apo.ucla.edu/JPF10884
</div>
<div><p><b>Help contact:</b> mlucas@mednet.ucla.edu</p>
</div>
<p>ABOUT UCLA</p>
<div>
<div><p>As a University employee, you will be required to comply with all applicable University policies and/or collective bargaining agreements, as may be amended from time to time. Federal, state, or local government directives may impose additional requirements.
</p><p>The University of California is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected status under state or federal law.</p>
<p>As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct.</p>
<ul><li>&ldquo;Misconduct&rdquo; means any violation of the policies or laws governing conduct at the applicant&rsquo;s previous place of employment, including, but not limited to, violations of policies or laws prohibiting sexual harassment, sexual assault, or other forms of harassment, discrimination, dishonesty, or unethical conduct, as defined by the employer.</li>
<li>UC Sexual Violence and Sexual Harassment Policy
</li><li>UC Anti-Discrimination Policy for Employees, Students and Third Parties
</li><li>APM - 035: Affirmative Action and Nondiscrimination in Employment</li>
</ul></div></div><p>JOB LOCATION</p>
<div>Los Angeles, CA</div></div>

Assistant Project Scientist (VA)

FullThrottle Labs Pvt Ltd

<p>Position Summary</p><p>As 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.</p><p>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.</p><p>Requirements</p><p>Core Technical Skills</p><p><b>*&nbsp;</b>*</p><p>1. Computational &amp;amp; Quantum Mechanical Methods</p><p><b>*&nbsp;</b>*</p><p>Electronic Structure &amp;amp; Quantum Methods</p><p>- <br/>Density Functional Theory (DFT)&nbsp;</p><p>- <br/>Ab initio Molecular Dynamics (AIMD)</p><p>- <br/>Time-dependent DFT (TDDFT) for excited states</p><p>- <br/>DFT+U for strongly correlated systems</p><p>- <br/>Hybrid functionals&nbsp;</p><p>- <br/>Hartree&ndash;Fock and post-HF methods (MP2, CCSD(T))</p><p>Molecular &amp;amp; Statistical Simulations</p><p>- <br/>Classical Molecular Dynamics (MD)</p><p>- <br/>Force-field development and validation</p><p>- <br/>Monte Carlo (MC) simulations</p><p>- <br/>Kinetic Monte Carlo (kMC) for surface reactions</p><p>- <br/>Machine Learning Force Fields ( Fairchem, Universal Forcefield, MACE)</p><p>Multiscale &amp;amp; Mesoscale Modeling</p><p>- <br/>Hierarchical nano &rarr; micro &rarr; meso &rarr; macro modeling</p><p>- <br/>QM&ndash;MM and QM&ndash;continuum coupling</p><p>- <br/>Microkinetic modeling and reaction networks</p><p>- <br/>Phase-field modeling</p><p>- <br/>Free energy methods (umbrella sampling, metadynamics)</p><p>2. Materials Simulation &amp;amp; Electronic Structure Modeling</p><p>- <br/>Bulk and surface DFT calculations</p><p>- <br/>k-point convergence, basis set testing</p><p>- <br/>Band structure, DOS, PDOS</p><p>- <br/>Phonons and lattice dynamics</p><p>- <br/>Elastic constants, thermal &amp;amp; mechanical properties</p><p>- <br/>Defect formation energies</p><p>- <br/>Phase stability &amp;amp; convex hulls</p><p>- <br/>Slab models and adsorption energies</p><p>- <br/>Reaction pathways using NEB / CI-NEB</p><p>Benchmarking &amp;amp; Validation</p><p>- <br/>Cross-code benchmarking across:</p><p>- <br/>DFT engines: VASP, Quantum ESPRESSO, CP2K, GPAW, CASTEP, Gaussian, ORCA</p><p>- <br/>MD engines: LAMMPS, GROMACS, NAMD</p><p>- <br/>ML potential</p><p>3. Materials Informatics &amp;amp; AI/ML</p><p>- <br/>Build ML models for materials &amp;amp; catalyst property prediction:</p><p>- <br/>Fairchem, Universal Forcefield, CGCNN, MEGNet, SchNet, e3nn, NequIP</p><p>- <br/>Transformer &amp;amp; foundation models for materials</p><p>- <br/>Curate datasets from:</p><p>- <br/>Materials Project, OQMD, NOMAD, JARVIS</p><p>- <br/>Develop ML surrogates for:</p><p>- <br/>Energy &amp;amp; force prediction</p><p>- <br/>Bandgap estimation</p><p>- <br/>Thermal &amp;amp; mechanical properties</p><p>- <br/>Catalyst screening &amp;amp; ranking</p><p>- <br/>Integrate ML pipelines with:</p><p>- <br/>DFT / MD workflows</p><p>- <br/>Quantum simulation pipelines</p><p>4. Simulation Workflow Engineering</p><p>- <br/>Build reproducible, automated workflows in Python for:</p><p>- <br/>High-throughput materials screening</p><p>- <br/>DFT&ndash;MD&ndash;CG-Mesoscale simulation pipelines</p><p>- <br/>Data extraction &amp;amp; post-processing</p><p>- <br/>Develop modular tools for:</p><p>- <br/>Structure parsing (CIF, POSCAR, XYZ, PDB)</p><p>- <br/>Geometry builders &amp;amp; surface generators</p><p>- <br/>Parameters generations&nbsp;</p><p>- <br/>Visualization (band structure, DOS, phonons, trajectories)</p><p>- <br/>Deploy workflows on:</p><p>- <br/>HPC clusters</p><p>- <br/>Cloud platforms (AWS, GCP)</p><p>- <br/>Containerized environments (Docker)</p><p>5. Research, Collaboration &amp;amp; Documentation</p><p>- <br/>Conduct literature reviews in:</p><p>- <br/>Computational materials</p><p>- <br/>Catalysis</p><p>- <br/>Semiconductors</p><p>- <br/>Alloy and Ceramics</p><p>- <br/>Polymers</p><p>- <br/>Quantum algorithms</p><p>- <br/>Design, execute, and analyze numerical experiments</p><p>- <br/>Prepare:</p><p>- <br/>Technical reports</p><p>- <br/>Internal whitepapers</p><p>- <br/>Presentations and datasets</p><p>- <br/>Collaborate closely with:</p><p>- <br/>Quantum hardware teams</p><p>- <br/>Algorithm developers</p><p>- <br/>AI/ML engineers</p><p>Specialization Tracks&nbsp;</p><p><b>*&nbsp;</b>*</p><p>A. DFT &amp;amp; Electronic Structure Specialization</p><p>- <br/>Advanced XC functional selection &amp;amp; benchmarking</p><p>- <br/>Strongly correlated systems (DFT+U, Hubbard models)</p><p>- <br/>Excited-state calculations (TDDFT, GW &ndash; exposure preferred)</p><p>- <br/>Defects, surfaces, and interfaces</p><p>- <br/>Electronic transport &amp;amp; conductivity modeling</p><p>B. Molecular Dynamics &amp;amp; Classical Simulations</p><p>- <br/>Classical MD simulations (LAMMPS, GROMACS)</p><p>- <br/>Force-field parameterization &amp;amp; validation</p><p>- <br/>Free energy calculations</p><p>- <br/>Reactive force fields (ReaxFF)</p><p>- <br/>ML-accelerated MD workflows</p><p>- <br/>Parameter generation for coarse-grained simulations</p><p>C. Catalysis Specialization</p><p>- <br/>Heterogeneous, homogeneous &amp;amp; electro-catalysis</p><p>- <br/>Reaction pathway identification</p><p>- <br/>Transition state searches (NEB, CI-NEB)</p><p>- <br/>Adsorption energies &amp;amp; surface thermodynamics</p><p>- <br/>Microkinetic modeling</p><p>- <br/>Applications:</p><p>- <br/>OER, ORR, HER</p><p>- <br/>Photocatalysis</p><p>- <br/>Single-atom &amp;amp; nanocluster catalysts</p><p>D. Polymers &amp;amp; Soft Matter Specialization</p><p>- <br/>DFT-based parameter extraction for polymers</p><p>- <br/>Multiscale polymer modeling (DFT, AA, CG)</p><p>- <br/>Dissipative Particle Dynamics (DPD)</p><p>- <br/>Monte Carlo Simulations</p><p>- <br/>Polymer blends, Polymer nanocomposites, surfactants, colloids</p><p>- <br/>Polymerization, degradation, crosslinking, morphology and aging studies</p><p>- <br/>Integration of DFT &rarr; MD &rarr; DPD&rarr;Phase field simulations pipelines</p><p>E. Quantum Computing for Materials Simulation</p><p>- <br/>Map materials Hamiltonians to qubits:</p><p>- <br/>Jordan&ndash;Wigner, Bravyi&ndash;Kitaev, parity mappings</p><p>- <br/>Work on quantum algorithms including:</p><p>- <br/>VQE for correlated materials</p><p>- <br/>Subspace Quantum Diagonalization (SQD)</p><p>- <br/>qEOM for excited states</p><p>- <br/>Quantum Phase Estimation</p><p>- <br/>QITE / Quantum Monte Carlo</p><p>- <br/>Analyze:</p><p>- <br/>Qubit requirements</p><p>- <br/>Circuit depth</p><p>- <br/>Noise &amp;amp; error budgets</p><p>- <br/>Design material-specific ans&auml;tze for NISQ devices and simulators</p><p><b>*&nbsp;</b>*</p><p>Software &amp;amp; Programming Skills</p><p>- <br/>DFT Codes: VASP, QE, CP2K, Gaussian, ORCA, CASTEP, ADF</p><p>- <br/>MD Codes: LAMMPS, GROMACS, NAMD, AMBER</p><p>- <br/>Visualization: VMD, VESTA, OVITO, Materials Studio, ASE</p><p>- <br/>Programming: Python (mandatory), Bash</p><p>- <br/>ML: PyTorch, TensorFlow, scikit-learn</p><p>- <br/>Infrastructure: HPC, MPI, Docker, Git, AWS / GCP</p><p>Soft Skills</p><p>- <br/>Strong analytical and first-principles thinking</p><p>- <br/>Ability to design reproducible scientific workflows</p><p>- <br/>Clear scientific communication</p><p>- <br/>High ownership and curiosity-driven research mindset</p><p>Educational Qualifications</p><p>- <br/>PhD (or pursuing PhD for intern role) in:</p><p>- <br/>Chemistry</p><p>- <br/>Materials Science</p><p>- <br/>Chemical Engineering</p><p>- <br/>Physics</p><p>- <br/>Computational Science or related STEM field</p><p>- <br/>Strong foundation in:</p><p>- <br/>Physical chemistry</p><p>- <br/>Quantum mechanics</p><p>- <br/>Statistical mechanics &amp;amp; thermodynamics</p><p>- <br/>Specialization in computational chemistry / materials modeling strongly preferred</p><p>Preferred Qualifications</p><p>- <br/>Publications or strong computational project portfolio</p><p>- <br/>Experience with HPC &amp;amp; large-scale simulations</p><p>- <br/>Prior work in:</p><p>- <br/>Materials discovery</p><p>- <br/>Catalysis</p><p>- <br/>Semiconductor</p><p>- <br/>Polymer modeling</p><p>- <br/>ML-driven materials science</p><p>- <br/>Exposure to quantum algorithms or hybrid quantum&ndash;classical workflows</p><p>Job Type: Full-time</p><p>Pay: ₹1,200,000.00 - ₹1,800,000.00 per year</p><p>Work Location: In person</p><p><b>Speak with the employer</b><br/>+91 9008078505</p>

Computational Materials Discovery Scientist

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