academic intern data science

Newton School

<div>
 
 
 About Newton School :&nbsp;
 
 
 Come be part of a rocketship that&rsquo;s creating a massive impact in the world of education!
 
 
 On one side you have over a million college graduates every year with barely 5% employability rates and on the other side, there are thousands of companies struggling to find talent. Newton School aims to bridge this massive gap
 
 through it&rsquo;s personalised learning platform. We are building an online university and solving the deep problem of employability of graduates.
 
 
 We have a strong core team consisting of alumni from IIT's and IIM&rsquo;s, having several years of industry experience in companies like Unacademy, Inmobi among others. On this mission, we are backed by some of the most respected investors around the world, - Nexus Venture Partners, RTP Global, Steadview Capital and a slew of angel investors including CRED&rsquo;s Kunal Shah, Flipkart&rsquo;s Kalyan Krishnamoorthy, Unacademy founders, Udaan&rsquo;s Sujeet Kumar among others.
 
 
 Socials: https://www.linkedin.com/school/newtonschool/ | newtonschool.co
 
 
 
 
 Role Description:
 
 
 As a Data Analyst Intern Intern at Newton School of Technology, you will work in the admissions team, interviewing potential candidates for our programs as well as analysing admissions for better intake quality. This internship is an excellent opportunity for individuals looking to gain hands-on experience in technical assessments and talent evaluation while contributing to shaping the future of tech talent.
 
 
 
 Responsibilities:
 
 
 <li>
 Assist in conducting technical and behavioral interviews for candidates.
 </li>
 <li>
 Evaluate candidates' coding, problem-solving, technical, and mathematical skills based on predefined criteria.
 </li>
 <li>
 Provide structured feedback for candidates to help the admissions team review their candidature for the programs.
 </li>
 <li>
 Working on creating advanced technical content for enrolled learners.
 </li>
 <li>
 Analytics and dashboard for admissions and webinars (part of mid funnel activities in the newton school&rsquo;s growth vertical)
 </li>
 
 
 
 Requirements:
 
 
 <li>
 Knowledge of SQL and Excel
 </li>
 <li>
 Pursuing or Recently completed a degree in Computer Science, Information Technology, or a related technical field.
 </li>
 <li>
 Basic knowledge of Coding, Analytics &amp; Algorithms, Problem-Solving Techniques, and Mathematical Concepts is needed.
 </li>
 <li>
 Strong communication and interpersonal skills.
 </li>
 <li>
 Interest in learning about interview processes and talent evaluation.
 </li>
 <li>
 Proactive attitude, attention to detail, and willingness to adapt to a fast-paced environment.
 </li>
</div>

Academic Intern (Data Science)

AB InBev GCC India

<div>
 
 
 Dreaming big is in our DNA. It&rsquo;s who we are as a company. It&rsquo;s our culture. It&rsquo;s our heritage. And more than ever, it&rsquo;s our future. A future where we&rsquo;re always looking forward. Always serving up new ways to meet life&rsquo;s moments. A future where we keep dreaming bigger. We look for people with passion, talent, and curiosity, and provide them with the teammates, resources and opportunities to unleash their full potential. The power we create together &ndash; when we combine your strengths with ours &ndash; is unstoppable. Are you ready to join a team that dreams as big as you do?
 
 
 
 
 
 
 
 AB InBev GCC was incorporated in 2014 as a strategic partner for Anheuser-Busch InBev. The center leverages the power of data and analytics to drive growth for critical business functions such as operations, finance, people, and technology. The teams are transforming Operations through Tech and Analytics.
 
 
 
 
 
 
 
 Do You Dream Big?
 
 
 
 
 
 
 
 We Need You.
 
 
 
 
 
 
 
 Job Description
 
 
 
 
 
 
 
 Job Title:
 
 Junior Data Scientist
 
 
 
 Location:
 
 Bangalore
 
 
 
 Reporting to:
 
 Senior Data Scientist
 
 
 
 
 
 
 
 
 
 1. Purpose of Role
 
 
 
 
 
 
 The Junior Data Scientist will support the development of analytical solutions that enable data-driven decision-making across the organization. The role focuses on building foundational skills in Python, SQL, and core data science workflows. It involves working closely with senior team members to prepare data, develop basic models, perform exploratory analysis, and contribute to documentation and reproducibility. This position is designed for individuals who can learn quickly, collaborate effectively, and apply structured problem-solving to business challenges.
 
 
 
 
 
 
 2. Key Tasks and Accountabilities
 
 
 
 
 
 <ul>
 <li>
 Assist in developing data science models and analytical components using Python with working knowledge of syntax, data structures, and foundational libraries such as pandas and numpy
 </li>
 <li>
 Conduct exploratory data analysis, basic feature creation, and initial statistical checks under the guidance of senior team members
 </li>
 <li>
 Write clean, readable, and well-organized code while following best practices shared by the team
 </li>
 <li>
 Collaborate with cross-functional teams to understand data needs, gather requirements, and support translation of business questions into analytical tasks
 </li>
 <li>
 Work with existing codebases to understand workflow logic, make incremental enhancements, and support maintenance tasks
 </li>
 <li>
 Use version control tools like Git for basic code commits, branching, and collaboration.
 </li>
 <li>
 Write simple to intermediate SQL queries to extract and prepare data from relational databases
 </li>
 <li>
 Support documentation of processes, datasets, code logic, and outputs for future use
 </li>
 <li>
 Learn and adopt standard development and data science methodologies including model evaluation, reproducibility, and simple automation of tasks
 </li>
 <li>
 Participate in team learning initiatives, staying curious about new tools, techniques, and best practices in analytics
 </li>
 </ul>
 
 
 
 
 
 3. Qualifications, Experience and Skills
 
 
 
 
 
 
 
 Education:
 
 
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in computer science, Information Systems, Mathematics, Statistics, Engineering, or a related discipline.
 </li>
 </ul>
 
 
 
 
 
 Experience:
 
 
 
 
 
 <ul>
 <li>
 1&ndash;3 years of experience in data science, analytics, or related technical roles, preferably with exposure to hands-on projects, internships, or academic assignments involving Python and data analysis.
 </li>
 </ul>
 
 
 
 
 
 Mandatory Skills:
 
 
 
 
 
 <ul>
 <li>
 
 Python Programming (Beginner to Intermediate):
 
 </li>
 <li>
 Basic proficiency with syntax, data structures, and use of core libraries such as pandas and numpy.
 </li>
 <li>
 
 Data Science Foundations:
 
 </li>
 <li>
 Understanding of descriptive statistics, basic model-building concepts, and feature preparation.
 </li>
 <li>
 
 SQL (Beginner to Intermediate):
 
 </li>
 <li>
 Ability to write queries for data extraction and manipulation.
 </li>
 <li>
 
 Version Control (Git):
 
 </li>
 <li>
 Familiarity with commits, branches, and collaborative code workflows.
 </li>
 <li>
 
 Code Adaptability:
 
 </li>
 <li>
 Ability to read and understand existing code and make minor enhancements.
 </li>
 </ul>
 
 
 
 
 
 Preferred (Good to Have) Skills
 
 
 
 
 
 <ul>
 <li>
 Exposure to Object-Oriented Programming (OOP) concepts in Python
 </li>
 <li>
 Basic knowledge of model evaluation techniques or lifecycle stages
 </li>
 <li>
 Awareness of test-driven development principles
 </li>
 <li>
 Experience with Jupyter notebooks, dashboards, or simple automation scripts.
 </li>
 </ul>
 
 
 
 
 
 
 
 
 And above all of this, an undying love for beer!
 
 
 
 
 We dream big to create future with more cheers
 
 .
 
</div>

Junior Data Scientist

Microsoft

<div>
 
 Overview
 
 
 
 Overview
 
 
 With the rapid acceleration of AI and the need to deliver trustworthy, high-performing models, Microsoft&rsquo;s Customer Experience (CXP) Data Science team is driving innovation at scale! Our mission is to advance AI capabilities through rigorous evaluations, fine-tuning, and large-scale experimentation to create intelligent, personalized experiences for customers worldwide. The CXP Data Science team is seeking passionate AI practitioners and data scientists to join agile, cross-functional teams working on cutting-edge model evaluation frameworks, optimization pipelines, and experimentation platforms that power Microsoft&rsquo;s AI ecosystem.
 
 
 We are looking for an
 
 Applied AI Scientist II
 
 to join our team! As a member of the Customer Experience Data Science organization at Microsoft, you will help us accelerate the company&rsquo;s own AI transformation. You will have the opportunity to partner directly with the engineering and product management groups responsible for managing the Dynamics 365 applications that power Microsoft&rsquo;s sales, marketing, and support platforms. You will apply advanced analytics, statistical modeling, machine learning and GenAI tools to uncover insights, drive action and deliver innovative solutions for complex business challenges.
 
 
 
 This Role Offers The Opportunity To
 
 
 
 <ul>
 <li>
 Collaborate across a diverse team of data scientists, engineers, and product managers
 </li>
 <li>
 Deepen your expertise in the evolving AI and ML landscape
 </li>
 <li>
 Drive meaningful impact for thousands of Microsoft sales, marketing and support platform users
 
 
 </li>
 </ul>
 Microsoft&rsquo;s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
 
 
 
 Responsibilities
 
 
 
 Responsibilities
 
 
 <ul>
 <li>
 Work with key stakeholders to understand the underlying business needs and formulate the needs into discrete, manageable problems with well-defined measurable objectives and outcomes.
 </li>
 <li>
 Transform formulated problems into implementation plans by defining success metrics, applying/creating the appropriate methods, algorithms, and tools, as well as delivering statistically valid and reliable results.
 </li>
 <li>
 Write robust, reusable, and extensible code to support analysis and modeling.
 </li>
 <li>
 Develop new ML and GenAI based models using advanced statistical, ML and LLM techniques.
 </li>
 <li>
 Lead the evaluation of various GenAI based solutions, diagnosing issues and identifying root causes to support potential fine-tuning or reinforcement learning based fixes.
 </li>
 <li>
 Use AI-powered tools in your daily work to accelerate coding, analysis, and other tasks.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 Qualifications
 
 
 
 Required/Minimum Qualifications (RQs/MQs)
 
 
 
 <ul>
 <li>
 Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research)
 </li>
 <ul>
 <li>
 OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
 </li>
 <li>
 OR equivalent experience.
 </li>
 </ul>
 <li>
 Expertise in Python , PySpark, and SQL, LLMs
 </li>
 <li>
 Exposure to ML development platforms such as Azure Machine Learning, Azure AI Foundry + Azure OpenAI
 
 </li>
 </ul>
 
 Additional Or Preferred Qualifications (PQs)
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Machine Learning, Data science, Mathematics, Statistics, Computer Science, or related field AND 5+ years related experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
 </li>
 <ul>
 <li>
 OR master&rsquo;s degree in data science, Mathematics, Statistics, Computer Science, or related field AND 4+ year(s) related experience
 </li>
 <li>
 OR Doctorate in Data Science, Mathematics, Statistics, Computer Science, or related field AND 3+ year(s) related experience
 </li>
 </ul>
 <li>
 Experience in Spark and ability to write/maintain/understand declarative Spark code and to cleanly write and maintain SQL. Knowledge of finer operational aspects of Spark such as setting optimal cluster size, executor memory, number of executors etc. and experience in Azure Synapse/Databricks (or similar).
 </li>
 <li>
 Expertise in ML development platforms such as Azure Machine Learning, Azure AI Foundry + Azure OpenAI
 </li>
 <li>
 1+ year(s) experience creating publications (e.g., patents, peer-reviewed academic papers).
 
 </li>
 </ul>
 This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
 
 
 Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about
 
 requesting accommodations.
 
</div>

Data & Applied Scientist II

Beckman Coulter Life Sciences

<div>
 
 In this role, you will have the opportunity to :
 
 
 
 <ul>
 <li>
 Perform Multi step Organic Synthesis.
 </li>
 <li>
 Purify different Organic compounds by various chromatography/other separation techniques such as column/flash/HPLC.
 </li>
 <li>
 Work on various analytical techniques such as HPLC, UPLC, GPC, UV-Vis, Fluorescence.
 
 
 </li>
 </ul>
 
 The Essential Requirements Of The Job Include
 
 
 
 
 M.Sc. in Organic Chemistry/Chemistry with minimum 1-2 years of work experience preferably in Organic Synthesis either in Chemical Industries/CROs/APIs or in academic research institutions.
 
 
 Good hands-on experience in,
 
 
 
 
 Multi-step Organic Synthesis. Especially, handling and optimization of acid-amine coupling, metal-catalyzed/metal free click Chemistry reactions.
 
 
 
 
 Knowledge and experience of data interpretation especially on the characterization of Organic compounds by NMR, LCMS, HPLC, UPLC etc.
 
 
 
 
 Good laboratory practices- record notebook maintenance.
 
 
 
 
 Travel, Motor Vehicle Record &amp; Physical/Environment Requirements:
 
 
 NO Travel is expected for this role. This would be a fully on-site role.
 
 
 
 
 Ability to lift/move or carry equipment like centrifuge rotors /solvents/buffers of 10-15 Liter/10-15 Kg capacity.
 
 
 
 
 It would be a plus if you also possess previous experience in:
 
 
 
 <ul>
 <li>
 Hands-on experience in HPLC/UPLC analytical method development &amp; optimization for new Organic compounds.
 </li>
 <li>
 Experience in handling, synthesis, characterization of Organic dyes and a good understanding of Photochemistry of the dyes.
 
 
 </li>
 </ul>
 Join our winning team today. Together, we&rsquo;ll accelerate the real-life impact of tomorrow&rsquo;s science and technology. We partner with customers across the globe to help them solve their most complex challenges, architecting solutions that bring the power of science to life.
 
 
 For more information, visit www.danaher.com.
</div>

Research Technician- Chemist

<div>
 
 Overview
 
 
 
 Come build community, explore your passions and do your best work at Microsoft with thousands of University interns from every corner of the world. This opportunity will allow you to bring your aspirations, talent, potential&mdash;and excitement for the journey ahead.
 
 
 As a Software Engineering Intern, you will work with teammates to solve problems and build innovative software solutions. You will apply your passion for customers and product quality as you provide technical guidance to Technical Program Managers and Product Managers. You will learn and adopt relevant new technologies, tools, methods, and processes to leverage in your solutions. This opportunity will enable you to advance your career by designing, developing, and testing next-generation software that will empower every person and organization on the planet to achieve more.
 
 
 At Microsoft, Interns work on real-world projects in collaboration with teams across the world, while having fun along the way. You&rsquo;ll be empowered to build community, explore your passions and achieve your goals. This is your chance to bring your solutions and ideas to life while working on cutting-edge technology.
 
 
 Microsoft&rsquo;s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Apply engineering principles to solve complex problems through sound and creative engineering.
 </li>
 <li>
 Work with appropriate stakeholders to determine user requirements for a feature.
 </li>
 <li>
 Quickly learns new engineering methods and incorporates them into work processes.
 </li>
 <li>
 Seek feedback and apply internal or industry best practices to improve technical solutions.
 </li>
 <li>
 Demonstrate skill in time management and completing software projects in a cooperative team environment.
 </li>
 <li>
 Review current developments and proactively seek new knowledge that will improve the availability, reliability, efficiency, observability, and performance of products while also driving consistency in monitoring and operations at scale.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Currently pursuing Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Engineering, or related field
 </li>
 <li>
 Must have at least 1 semester/term remaining following the completion of the internship
 </li>
 <li>
 Ability to demonstrate an understanding of computer science fundamentals, including data structures and algorithms
 
 
 </li>
 </ul>
 This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
 
 
 Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about
 
 requesting accommodations.
 
</div>

Software Engineering INTERN

Mindrift

<div>
 
 
 This opportunity is only for candidates currently residing in the specified country. Your location may affect eligibility and rates. Please submit your resume in English and indicate your level of English.
 
 
 
 
 At Mindrift, innovation meets opportunity. We believe in using the power of collective human intelligence to ethically shape the future of AI.
 
 
 
 What We Do
 
 
 
 The Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe.
 
 
 
 About The Role
 
 
 
 We're looking for someone who can design
 
 realistic and structured evaluation scenarios
 
 for LLM-based agents. You'll create test cases that simulate human-performed tasks and define gold-standard behavior to compare agent actions against. You'll work to ensure each scenario is clearly defined, well-scored, and easy to execute and reuse. You'll need a sharp analytical mindset, attention to detail, and an interest in how AI agents make decisions.
 
 
 Although every project is unique, you might typically:
 
 
 <ul>
 <li>
 Create structured test cases that simulate complex human workflows
 </li>
 <li>
 Define gold-standard behavior and scoring logic to evaluate agent actions.
 </li>
 <li>
 Analyze agent logs, failure modes, and decision paths
 </li>
 <li>
 Work with code repositories and test frameworks to validate your scenarios
 </li>
 <li>
 Iterate on prompts, instructions, and test cases to improve clarity and difficulty
 </li>
 <li>
 Ensure that scenarios are production-ready, easy to run, and reusable
 
 
 </li>
 </ul>
 
 How To Get Started
 
 
 
 Simply apply to this post, qualify, and get the chance to contribute to projects aligned with your skills, on your own schedule. From creating training prompts to refining model responses, you'll help shape the future of AI while ensuring technology benefits everyone.
 
 
 
 Requirements
 
 
 
 <ul>
 <li>
 Bachelor's and/or Master's Degree in Computer Science, Software Engineering, Data Science / Data Analytics, Artificial Intelligence / Machine Learning, Computational Linguistics / Natural Language Processing (NLP), Information Systems or other related fields.
 </li>
 <li>
 Background in QA, software testing, data analysis, or NLP annotation
 </li>
 <li>
 Good understanding of test design principles (e.g., reproducibility, coverage, edge cases)
 </li>
 <li>
 Strong written communication skills in English
 </li>
 <li>
 Comfortable with structured formats like JSON/YAML for scenario description
 </li>
 <li>
 Can define expected agent behaviors (gold paths) and scoring logic
 </li>
 <li>
 Basic experience with Python and JS
 </li>
 <li>
 Curious and open to working with AI-generated content, agent logs, and prompt-based behavior
 
 
 </li>
 </ul>
 
 Nice to Have
 
 
 
 <ul>
 <li>
 Experience in writing manual or automated test cases
 </li>
 <li>
 Familiarity with LLM capabilities and typical failure modes
 </li>
 <li>
 Understanding of scoring metrics (precision, recall, coverage, reward functions)
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 Contribute on your own schedule, from anywhere in the world. This opportunity allows you to:
 
 
 <ul>
 <li>
 Get paid for your expertise, with rates that can go up to $12/hour depending on your skills, experience, and project needs
 </li>
 <li>
 Take part in a flexible, remote, freelance project that fits around your primary professional or academic commitments
 </li>
 <li>
 Participate in an advanced AI project and gain valuable experience to enhance your portfolio
 </li>
 <li>
 Influence how future AI models understand and communicate in your field of expertise
 </li>
 </ul>
</div>

Freelance AI Evaluation Scenario Writer

Scouto AI

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

Computational Materials Discovery Scientist

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