computational scientist

Scouto AI

<div>
 Position Summary
 <br/>
 <br/>
 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.
 <br/>
 <br/>
 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.
 <br/>
 <br/>
 <strong>
  Requirements
  <br/>
  <br/>
 </strong>
 Core Technical Skills
 <br/>
 <br/>
 <ul>
  <li>
   Computational &amp; Quantum Mechanical Methods
   <br/>
   <br/>
  </li>
 </ul>
 Electronic Structure &amp; Quantum Methods
 <br/>
 <br/>
 <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))
   <br/>
   <br/>
  </li>
 </ul>
 Molecular &amp; Statistical Simulations
 <br/>
 <br/>
 <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)
   <br/>
   <br/>
  </li>
 </ul>
 Multiscale &amp; Mesoscale Modeling
 <br/>
 <br/>
 <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
   <br/>
   <br/>
  </li>
 </ul>
 Benchmarking &amp; Validation
 <br/>
 <br/>
 <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
    <br/>
   </li>
  </ul>
 </ul>
 Specialization Tracks
 <br/>
 <br/>
 <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>
  <li>
   Analyze:
  </li>
  <ul>
   <li>
    Qubit requirements
   </li>
   <li>
    Circuit depth
   </li>
   <li>
    Noise &amp; error budgets
   </li>
  </ul>
  <li>
   Design material-specific ans&auml;tze for NISQ devices and simulators
   <br/>
  </li>
 </ul>
 Software &amp; Programming Skills
 <br/>
 <br/>
 <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
   <br/>
   <br/>
  </li>
 </ul>
 Soft Skills
 <br/>
 <br/>
 <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
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Educational Qualifications
  <br/>
  <br/>
 </strong>
 <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
   <br/>
  </li>
 </ul>
 <strong>
  Preferred Qualifications
  <br/>
  <br/>
 </strong>
 <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
   <br/>
  </li>
 </ul>
 Skills: ml,dft,materials,simulations,modeling
</div>


Computational Materials Discovery Scientist

King Abdullah University of Science and Technology

179324
<br><div></div><div><div><div><div><div><div><div><div><div><div>King Abdullah University of Science and Technology: Postdoc Positions: Physical Science and Engineering Division (postdoc): Energy Resources and Petroleum Engineering (Postdoc)
</div></div></div><div><div><h3 class="jobSectionHeader"><b>Location
</b></h3><div>King Abdullah University of Science and Technology (KAUST)
</div></div><div><h3 class="jobSectionHeader"><b>Open Date
</b></h3><div>Dec 18, 2025
</div></div></div><div><div><h3 class="jobSectionHeader"><b>Description
</b></h3><div><div><p>The design of industrial membrane separation materials requires advanced computation methods, such as computational fluid dynamics and computational chemistry, to design, analyze, and predict the properties and performance of these materials. This area also requires experimental studies by providing insights from molecular levels to continuous pore scale level. The modeling of porous membrane usually requires computationally expensive modeling approaches such as molecular dynamics simulations (MD), computational fluid dynamics (CFD) to understand how porous structures and operating conditions can impact membrane performance. Therefore, this objective of this research is develop efficient algorithms and models based on deep learning to accelerate the physics simulation for membrane relevant processes, which can be based on physics-informed neural network, data-driven models, and hybrid simulation models. These developed models can ultimately be deployed for industrial applications of membrane design and manufacturing processes.</p>
<p>
The successful candidate will be based at Inorganic Membranes Research Group at KAUST, under the leadership of Professor Zhiping Lai, and will collaborate closely with Professor Bicheng Yan (KAUST).</p>
<p><b>
Benefits:</b></p>
<p>
Applications are sought for a one-year postdoc position (extendable). The position will include a competitive salary based on the candidate&rsquo;s qualifications; benefits include medical and dental insurance, free furnished housing on the KAUST campus, annual travel allowance to visit home country, annual paid vacation, and other generous benefits.</p></div>
</div>
</div></div><div><div><h3 class="jobSectionHeader"><b>Qualifications
</b></h3><div><div><p><b>Education:</b></p>
<p>
A Ph.D. degree in computational mathematics, computational mechanics, computational chemistry, machine/deep learning or closely related fields. The candidate must have completed all Ph.D. requirements by commencement of the appointment and be within 5 years of completion of the Ph.D.</p>
<p><b>
Minimum Job Requirements:</b></p>
<p>
(1) Experience in computational mechanics, computational chemistry for membrane materials</p>
<p>
(2) Experience with code development</p>
<p>
(3) Publications in refereed journals and record of successful research in a collaborative team environments</p>
<p><b>
Desired Qualification:</b></p>
<p>
(1) Experience with Python, Julia</p>
<p>
(2) Experience in scientific machine learning, deep learning and computer vision</p>
<p>
(3) Experience in developing physics simulation models with FEniCS, COMSOL, Ansys</p></div>
</div>
</div></div><div><div><h3 class="jobSectionHeader"><b>Application Instructions
</b></h3><div><div><p><b>How to Apply?</b></p>
<p>
Please send the following documents as a package and directly email to Prof. Zhiping Lai by zhiping.lai@kaust.edu.sa and Prof. Bicheng Yan by bicheng.yan@kaust.edu.sa with email title: PorousMaterial_Postdoc_Applicant_FirstName_LastName,</p>
<div>
1. CV;</div>
<div>
2. Cover letter highlighting your research experience and justification to fit this position;</div>
<div>
3. List of publications;</div>
<div>
4. Copy of your official Ph.D. degree;</div>
<div>
5. Three contacts of reference;</div>
<p>
6. Indication of your earliest available date.</p></div>
</div>
</div></div></div><div><div><div><h3 class="jobSectionHeader"><b>Application Process
</b></h3><div>This institution is using Interfolio's Faculty Search to conduct this search. Applicants to this position receive a free Dossier account and can send all application materials, including confidential letters of recommendation, free of charge.</div></div></div></div></div></div></div></div></div></div><p></p>

Scientific Machine Learning to Simulate Complex Physics Processes in Porous Materials

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>
What role you will play in our team</b></h2></div><p></p><div><p><br>
We are looking to hire candidates to work on challenging technology and engineering problems that span oil and gas exploration &amp; production, chemicals/fuels/lubricants products and low carbon solutions. A successful candidate would understand a business problem (both commercially and technically), translate it into a computational, data science or machine learning problem and apply engineering, numerical, data science and programming skills to tackle it. The Machine Learning Engineer will work as part of a team to design, develop, deploy and sustain data science solutions that are scalable, reproducible and with commercial-grade quality.</p></div></div><div><div><h2 class="jobSectionHeader"><b>
What you will do</b></h2></div><p></p><div><br>
<ul><li>
Applies software development practices, DevOps skills and Machine Learning (ML) techniques to orchestrate an end-to-end machine learning workflow that effectively brings ML models to production.</li><li>
Participates in scoping of deployment of new data science solutions and implements the appropriate solution design.</li><li>
Sustain data science solutions by enabling continuous ML model and/or service performance monitoring, training, and re-training of models, including the implementation of proactive alerting methods.</li><li>
Works effectively with computational scientists, data scientists, engineers, software developers, and domain experts across the globe to develop and apply computational and data science solutions in support of our business.</li></ul></div></div><div><div><h2 class="jobSectionHeader"><b>
About You</b></h2></div><p></p><div><p><b><br>
Skills and Qualifications</b></p><br>
<p></p><ul><li>
Bachelor&rsquo;s degree from a recognized university in Computer Science, IT, Applied Mathematics, Engineering or related disciplines with minimum 7.0 CGPA or equivalent.</li><li>
Minimum 3 years of experience in Data Science and Machine Learning or related computational domain.</li><li>
Competent to expert level programming experience in C/C++/Python.</li><li>
Strong foundation in application design.</li><li>
Experience with refactoring legacy code and leveraging third-party libraries/APIs during software development.</li><li>
Experience with Source code version control (Git), Azure Cloud platform and containers, Databricks and MLflow.</li><li>
Continuous Integration and Continuous Deployment.</li><li>
Familiarity with statistical analysis, regression and classification.</li></ul></div></div><div><div><h2 class="jobSectionHeader"><b>
Preferred Qualifications / Experience</b></h2></div><p></p><div><br>
<ul><li>
Experience with time series analysis, computer vision, natural language processing.</li><li>
Knowledge or hands on experience on Matlab &amp; SQL.</li><li>
Strong written and verbal communication skills.</li><li>
Prior knowledge of commercial software development and/or experience in commercial software teams.</li><li>
Familiarity with Oil and Gas Industry.</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><br>
<p></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 <b>ExxonMobil India</b> and <b>Energy Factor India</b><b>.</b></li><li>
Follow us on <b>LinkedIn</b> and <b>ExxonMobil (@exxonmobil) &bull; Instagram photos and videos</b><b>
</b></li><li>Like us on <b>Facebook</b></li><li>
Subscribe our channel at <b>YouTube</b></li></ul></div></div><p></p><div><div><h2 class="jobSectionHeader"><b><br>
EEO Statement</b></h2></div><p></p><div><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></div></div><div><div><h2 class="jobSectionHeader"><b><br>
Business solicitation and recruiting scams</b></h2></div><p></p><div><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>

Machine Learning Engineer

Aramco Overseas Company

<p></p><div><div><div><div><div><div><div><b>Job Req ID: </b>17281
</div></div></div></div><div><div><div><div><b>Description:
</b><div><b>Aramco energizes the world economy.</b></div>
<div>Aramco occupies a special position in the global energy industry. We are one of the world&rsquo;s largest producers of hydrocarbon energy and chemicals, with among the lowest Upstream carbon intensities of any major producer.</div>
<div>With our significant investment in technology and infrastructure, we strive to maximize the value of the energy we produce for the world along with a commitment to enhance Aramco&rsquo;s value to society.</div>
<div>Headquartered in the Kingdom of Saudi Arabia, and with offices around the world, we combine market discipline with a generations&rsquo; spanning view of the future, born of our nine decades experience as responsible stewards of the Kingdom&rsquo;s vast hydrocarbon resources. This responsibility has driven us to deliver significant societal and economic benefits to not just the Kingdom, but also to a vast number of communities, economies, and countries that rely on the vital and reliable energy that we supply.</div>
<div>We are one of the most profitable companies in the world, as well as amongst the top five global companies by market capitalization.</div>
<div><div><div><div><b>
Overview</b></div>
</div><div><div>
We are seeking Computational Research Expert with a strong background in Optimization and Control Theory to join our Research &amp; Development Center (R&amp;DC).</div><br>
<div></div>
<div>
R&amp;DC conducts strategic research, development and demonstration programs in support of Aramco&rsquo;s drive for innovation.</div><br>
<div></div>
<div>
Your primary role is to accelerate the deployment of next-generation technologies by building scalable digital platforms powered by emerging computing paradigms. You will also enable transformative solutions that focus on addressing critical challenges in CO₂ reduction and sustainable energy systems.</div></div></div><div><div><div><b>
Key Responsibilities</b></div>
</div><div><div>
As the successful candidate you will be required to perform the following:</div>
<ul>
<li>Designing and implementing advanced optimization and control frameworks to solve large-scale, multi-objective energy challenges.</li>
<li>Identify collaboration opportunities with leading institutes and organizations</li>
<li>Liaise with key stakeholders to ensure in-house technology options deployment.</li>
<li>Collaborate with cross-functional teams and provide technical guidance and mentorship.</li>
<li>Contribute to technical documentation, patents, and publications</li>
</ul></div></div><div><div><div><b>Minimum Requirements</b></div>
</div><div><ul><li>As a successful candidate you will hold a Bachelor degree in Science or Engineering. A PhD is also required.</li>
<li>You should have a minimum of 5 years of experience.</li>
<li>You will have a proven record pf conducting advanced technical projects with an ability to connect with basic science research with industrial applocations.</li>
<li>You will have skills in Differentiable programming, Computational Fluid Dynamics, Optimization algorithms, Adjoint method, Generative AI, High performance computing. Coding skills in in JAX, Pytorch, Julia, C++ are also necessary.</li>
</ul></div></div><div><div><div><b>Work Location and Work Schedule
</b></div></div><div><div>Work location: Within Saudi Arabia &ndash; To be specified in Job offer</div>
<div>
Work schedule: Full Time - To be specified in Job offer</div></div></div><div><div><div><b>
Job Posting Duration</b></div>
</div><div><div>
Job posting start date: 12/18/2025</div>
<div>
Job posting end date: 12/31/2026</div></div></div></div><div><b>
Working environment
</b></div><div>Our high-performing employees are drawn by the challenging and rewarding professional, technical and industrial opportunities we offer, and are remunerated accordingly.
</div><div>At Aramco, our people work on truly world-scale projects, supported by investment in capital and technology that is second to none. And because, as a global energy company, we are faced with addressing some of the world&rsquo;s biggest technical, logistical and environmental challenges, we invest heavily in talent development.
</div><div>We have a proud history of educating and training our workforce over many decades. Employees at all levels are encouraged to improve their sector-specific knowledge and competencies through our workforce development programs &ndash; one of the largest in the world.</div><br>
<div></div>
</div></div></div></div><div><div><div><div><b>Country/Region: </b>SA</div></div></div></div></div></div></div><p></p>

Computational Research Expert (Optimization and Control)

Amgen

<div><h2 class="jobSectionHeader"><b>What you will do</b></h2><p><b>
Let&rsquo;s do this. Let&rsquo;s change the world.</b><br>
We are seeking a highly qualified and motivated Principal Data Scientist with deep expertise in computational biology to join the Bioinformatics Technologies team within Amgen&rsquo;s Automation, Research Data Systems, Informatics, and AI (ARIA) organization. ARIA is a multidisciplinary group embedded within Amgen&rsquo;s discovery engine, applying advanced digital technologies to accelerate the path from target inception through drug development. Within ARIA, Bioinformatics Technologies develops and deploys innovative computational methods that enhance target identification, mechanistic characterization, early validation, and therapeutic discovery.</p><p><br>
In this role, you will lead and expand computational and systems biology capabilities that support Amgen&rsquo;s pre-clinical discovery engine, with a strong emphasis on generating insights from functional genomics, multimodal omics, and other high-dimensional biological datasets. You will provide both scientific and people leadership to a team of data scientists applying next-generation computational, statistical, and AI/ML approaches to identify therapeutic targets, uncover biomarkers, refine disease hypotheses, and guide experimental strategies across early research. This position plays a critical role in strengthening the data-driven foundation of Amgen&rsquo;s pre-clinical value chain by elevating analytical rigor and improving interpretation of complex biological data.</p><p></p><p>
The ideal candidate brings strong analytical aptitude, deep technical expertise in computational sciences, and a solid theoretical foundation in advanced statistical and machine learning methods. These skills must be complemented by a strong understanding of molecular biology and functional genomics, along with a proven track record of innovative and collaborative research demonstrated through impactful peer-reviewed publications.<br>
<br>
RESPONSIBILITIES:</p><ul><li>
Mentor junior biological data scientists working on functional genomics, disease biology, and multi-omics analytics to support pre-clinical target discovery and early validation.</li><li>
Develop, implement, and apply advanced computational / AI/ML / statistical methods and workflows to analyze high-dimensional multi-modal omics datasets for target identification, mechanism elucidation, and biomarker hypothesis generation.</li><li>
Drive innovation in design and execution of computational analyses supporting high-throughput screens to map gene-phenotype relationships, prioritize candidate targets, and guide experimental follow-up.</li><li>
Collaborate with experimental biology and translational research teams to align computational predictions with biological context, guide study design, and translate computational insights into actionable pre-clinical hypotheses.</li><li>
Design and implement computational workflows for cutting-edge functional genomics and multi-omics technologies (e.g., single-cell, spatial, long-read sequencing, phenotypic and virtual perturbation screens), using advanced AI/ML/deep-learning methods to simulate cellular responses, derive mechanistic insights, and prioritize therapeutic hypotheses for preclinical validation.</li><li>
Foster a culture of scientific innovation and collaboration within the team by encouraging creative problem-solving, continuous learning, cross-disciplinary exchange, and reproducible experimentation with emerging computational and omics methodologies.</li><li>
Communicate project results and data-driven recommendations to stakeholders and cross-functional partners.</li><li>
Monitor, review, and critically interpret published computational research in the field of computational biology, bioinformatics, and systems biology.<br>
</li></ul><h2 class="jobSectionHeader"><b>
Win</b></h2><p><b>
What we expect of you</b></p><p>
We are all different, yet we all use our unique contributions to serve patients. The dynamic professional we seek is a scientist with these qualifications.</p><h2 class="jobSectionHeader"><b><br>
Basic Qualifications:</b></h2><p>
Doctorate degree in computer science, biomedical data science, computational biology, bioinformatics, or systems biology; preferably with post-doctoral training and industry experience</p><h2 class="jobSectionHeader"><b>
Or</b></h2><p>
Master&rsquo;s degree and 6+ years of biomedical data science, computational biology, bioinformatics, systems biology or related field</p><h2 class="jobSectionHeader"><b>
Or</b></h2><p>
Bachelor&rsquo;s degree and 8+ years of biomedical data science, computational biology, bioinformatics, systems biology, or related field</p><h2 class="jobSectionHeader"><b><br>
Preferred Qualifications:</b></h2><ul><li>
Demonstrated track record of scientific productivity in computational biology, bioinformatics, or related research settings.</li><li>
Track record of mentoring, team leadership or supervision within a formal or matrix structure, preferably in a multidisciplinary environment, helping to grow junior scientists and foster innovation, collaboration, and scientific rigor within a data-science team.</li><li>
Proven experience working at the intersection of computational biology, functional genomics, and drug-discovery/preclinical research (e.g., target identification, biomarker discovery, mechanistic modeling).</li><li>
Demonstrated success in applying machine learning, deep learning, generative modeling, topological data analysis, or causal inference to multimodal omics, functional genomics, single-cell, spatial, or long-read sequencing data to generate biologically meaningful hypotheses.</li><li>
Strong programming and data-science skills, including proficiency in Python and/or R; demonstrated experience with large-scale data analysis and high-dimensional biological data; and comfort working in high-performance or cloud computing environments under modern data-science workflows.</li><li>
Familiarity with molecular and disease biology, with the ability to contextualize computational findings in therapeutic discovery.</li><li>
Excellent analytical and communication skills, with the ability to extract and clearly present insights from complex data to diverse audiences with rigor and accuracy.</li><li>
Strong interpersonal and collaborative skills with demonstrated ability to thrive in cross-functional teams and effectively present results to diverse audiences.</li><li>
Creative, open-minded, and passionate about research, with a proven record of innovative algorithm and model development demonstrated through impactful publications, patents, or widely adopted tools.</li></ul></div>

Principal Data Scientist - Computational & Systems Biology

General Dynamics Information Technology

<div></div><div><div><div>Clearance Level<div>
None</div></div><div></div><div>
Category<div>
IT Infrastructure and Operations</div></div><div></div><div>
Locations<div>
Remote, Working from Maryland<br>
Remote, Based in District of Columbia<br>
Remote, Based in Virginia</div><i>
(</i><i>Hybrid Workplace</i><i>)</i></div><div><p>
</p></div></div><div><p>
Key Skills For Success</p><div><div>
High Performance Computing (HPC)</div></div><div><div>
High-Performance Computing (HPC) Systems</div></div><div><div>
Scientific Research</div></div></div><div><div><div><div><div><div><p>
SHARE</p></div></div></div><div></div><div><p>
REQ#: RQ210426</p><p>
Public Trust: NACI (T1)
</p><p>Requisition Type: Regular
</p><p>Your Impact</p><p>
Own your opportunity to work alongside federal civilian agencies. Make an impact by providing services that help the government ensure the well being of U.S. citizens.</p><p>
Job Description</p><div><p>
GDIT is seeking an experienced Scientific Computing Manager to join our program supporting the biomedical research community for our customer with the National Institute of Allergy and Infectious Diseases (NIAID).
</p><p></p><p>As our Scientific Computing Manager, you will be responsible for developing and delivering comprehensive infrastructure and application/end user support services to the NIAID research community. This includes architecture, implementation and ongoing operations of multiple HPC clusters, scientific storage, scientific instrumentations, and application support services for a catalog of over 600 open source, COTS, and custom applications. Your team will provide high-touch, consultative end user support to a research community of approximately 4500. You must be able to simultaneously manage various duties such as project management, operations and maintenance, and team management to ensure customer satisfaction while enhancing the caliber of services delivered.</p><p></p><p>
** PLEASE NOTE: This position is primarily remote; however, you must reside within commuting distance to the client site in Rockville, MD and be able to be onsite from 1 day a week to 1 week a month to meet contractual obligations and project needs. Possible travel to the Montana location.</p><p></p>
Responsibilities and Duties:<ul><li>
Provides day to day team management and oversight of operations, project execution and service delivery for scientific computing infrastructure, application workloads and scientific instrumentation teams</li><li>
Ensures scientific computing service delivery is aligned with program and customer goals; develops strategic roadmaps and tracks KPI&rsquo;s</li><li>
Manages 3 to 4 direct reports and a total team of up to 15 people, including hiring, performance management, training, and mentoring. This includes delegating tasks, providing direction, and inspiring collaboration and teamwork</li><li>
Responsible for multiple High Performance Computing (HPC) clusters including all compute, storage and supporting applications</li><li>
Supports requirements gathering from internal and external stakeholders</li><li>
Manage daily operations, tickets, outages and continuous improvement in operational efficiency</li><li>
Work closely with Program Leadership, Federal Leadership, Researchers Enterprise Architecture and PMO to align and coordinate efforts and provide transparency</li></ul>
Required Qualifications and Duties:<ul><li>
Masters and 5+ years or equivalent combination of education and experience</li><li>
Experience with HPC clusters</li><li>
Experience with comprehensive scientific computing infrastructure, scientific data storage and/or scientific instrumentation support</li><li>
Experience supporting scientific applications and workflows including HPC job optimization, dedicated platform support, specialized computational systems, and computational pipelines</li><li>
Experience leading cross-functional teams including scientists and engineers</li><li>
Experience with managing multiple complex activities simultaneously</li><li>
Experience presenting complex concepts to various stakeholders</li></ul>
Desired Qualifications and duties:<ul><li>
Education or experience in life or physical sciences, PhD preferred</li><li>
Experience working directly with researchers for support and troubleshooting</li><li>
Experience with HPC systems and tooling like SLURM, GPFS, Globus</li><li>
Experience with scientific research tooling like CryoSPARC, JupyterHub</li><li>
Experience deploying and managing cloud based scientific computing resources</li><li>
Experience running AI/ML and scientific research workloads</li><li>
Excellent written and verbal communication skills</li></ul><p></p><p>
#GDITFedHealthJobs</p><p>
#GDITPriority</p>
</div></div><div><div><div><p>Work Requirements</p></div></div><div></div><div><div>
Years of Experience<div>
5 + years of related experience</div><ul><li>may vary based on technical training, certification(s), <i>or</i> degree</li></ul></div><div></div><div>
Certification</div><p></p><div>
Travel Required<div>
Less than 10%</div></div></div></div></div><div><p>
Salary and Benefit Information</p><div>
The likely salary range for this position is $161,500 - $218,500. This is not, however, a guarantee of compensation or salary. Rather, salary will be set based on experience, geographic location and possibly contractual requirements and could fall outside of this range.<br>
View information about benefits and our total rewards program.</div><p>
About Our Work</p><div>
We are GDIT. A global technology and professional services company that delivers technology and mission services to every major agency across the U.S. government, defense and intelligence community. Our 30,000 experts extract the power of technology to create immediate value and deliver solutions at the edge of innovation. We operate across over 50 countries worldwide, offering leading capabilities in digital modernization, AI/ML, cloud, cyber and application development. Together with our customers, we strive to create a safer, smarter world by harnessing the power of deep expertise and advanced technology.</div><div>
Join our Talent Community to stay up to date on our career opportunities and events at gdit.com/tc.</div><div><i>
Equal Opportunity Employer / Individuals with Disabilities / Protected Veterans</i></div></div></div></div></div>

Scientific Computing Manager

A.P. Moller - Maersk

<div>
 <strong>
  AI/ML Scientist (Operations research/Optimization/Simulation)
  <br/>
  <br/>
 </strong>
 <strong>
  A.P. Moller - Maersk
  <br/>
  <br/>
 </strong>
 A.P. Moller &ndash; Maersk is the global leader in container shipping services. The business operates in 130 countries and employs 80,000 staff. An integrated container logistics company, Maersk aims to connect and simplify its customers&rsquo; supply chains.
 <br/>
 <br/>
 Today, we have more than 180 nationalities represented in our workforce across 131 Countries and this mean, we have elevated level of responsibility to continue to build inclusive workforce that is truly representative of our customers and their customers and our vendor partners too.
 <br/>
 <br/>
 The team - who are we:
 <br/>
 <br/>
 We are an ambitious team with the shared passion to use data, data science (DS), machine learning (ML), advanced simulation, optimization and engineering excellence to make a difference for our customers.
 <br/>
 <br/>
 We are a team, not a collection of individuals. We value our diverse backgrounds, our different personalities and strengths &amp; weaknesses. We value trust and passionate debates. We challenge each other and hold each other accountable. We uphold a caring feedback culture to help each other grow, professionally and personally.
 <br/>
 <br/>
 We are now seeking a new team member who is excited about developing advanced simulation models,optimization algorithms and AI/ML solutions that create operational insights for container shipping terminals
 <br/>
 <br/>
 worldwide, helping them optimize container handling, yard operations, vessel operations, and drive efficiency
 <br/>
 <br/>
 and business value.
 <br/>
 <br/>
 We Offer - This Is What You Get
 <br/>
 <br/>
 You will be part of the APM Terminals team within Global data and analytics (GDA), responsible for developing and delivering advanced simulation models, optimizations and AI/ML models for container shipping
 <br/>
 <br/>
 terminals. As an AI/ML Scientist, you will have a leading role in designing, building, maintaining, and
 <br/>
 <br/>
 iterating on products that directly impact terminal operations.
 <br/>
 <br/>
 This position offers a unique opportunity to develop and apply your deep knowledge of simulation, optimization, data science methods, software engineering, and modern AI development tools to create
 <br/>
 <br/>
 operational and strategic insights that are transforming container terminal operations globally.
 <br/>
 <br/>
 This is an exciting time to join a growing and dynamic team that solves some of the toughest problems in
 <br/>
 <br/>
 terminal operations and builds the future of container shipping. We offer a unique opportunity to impact global trade via world-leading container terminals. We focus on our people and the right candidate will have broad
 <br/>
 <br/>
 possibilities to further develop competencies in an environment characterized by change and continuous Progress.
 <br/>
 <br/>
 Key Responsibilities
 <br/>
 <br/>
 <ul>
  <li>
   Design, implement and deliver advanced simulation models and optimization solutions for terminal operations including container handling equipment efficiency, yard positioning strategies, vessel loading/unloading sequencing, and truck routing.
  </li>
  <li>
   Develop and maintain efficient applied engineering solutions that solve real-world operational challenges at container terminals globally.
  </li>
  <li>
   Build both operational tools for day-to-day terminal operations and strategic models for long-term planning and decision-making.
  </li>
  <li>
   Work with relevant stakeholders to understand terminal operational dynamics and business processes, incorporating their needs into products to enhance value delivery.
  </li>
  <li>
   Collaborate and communicate model rationale, results and insights with product teams, leadership and business stakeholders to roll out solutions to production environments.
  </li>
  <li>
   Analyse data, measure delivered value, and continuously evaluate and improve models to increase effectiveness and operational impact.
   <br/>
   <br/>
  </li>
 </ul>
 To do this job, we imagine you have:
 <br/>
 <br/>
 <ul>
  <li>
   5+ years of industry experience in building and delivering simulation models, optimization solutions, or data science products.
  </li>
  <li>
   PhD or M.Sc. in Operations Research, Industrial Engineering, Machine Learning, Statistics, Applied Mathematics, Computer Science, or other field related to algorithms and data (or equivalent experience).
  </li>
  <li>
   Strong experience in simulation modeling and optimization, particularly in operational environments with complex dynamics.
  </li>
  <li>
   Research or industry experience in one or more: Discrete event simulation, Combinatorial optimization problems (e.g., scheduling, vehicle routing, bin packing, sequencing), Continuous optimization problems (e.g., linear programming, mixed-integer programming, convex programming), AI/ML methods for operational problems, Prescriptive analytics (e.g., stochastic optimization, reinforcement learning).
  </li>
  <li>
   Experience with AI development tools and code assistants (GitHub Copilot, Cursor, Claude Code, or similar) for enhanced productivity.
  </li>
  <li>
   Excellent record of delivery using Python and technologies like Git, JIRA, etc.
  </li>
  <li>
   Ability to understand complex operational systems and translate business requirements into effective technical solutions.
  </li>
  <li>
   Strong communication skills with ability to work independently with stakeholders while liaising and reviewing with the team.
  </li>
  <li>
   Experience working with cloud environments.
   <br/>
   <br/>
  </li>
 </ul>
 Nice to have:
 <br/>
 <br/>
 <ul>
  <li>
   Experience in container terminal operations, port logistics, or similar operational environments with complex resource allocation and scheduling dynamics.
  </li>
  <li>
   Familiarity with container handling equipment, yard operations, or vessel operationsExperience in material handling, manufacturing operations, or other domains involving physical asset optimization and sequencing problems.
  </li>
  <li>
   Experience developing and interacting with generative AI models.
   <br/>
   <br/>
  </li>
 </ul>
 Maersk is committed to a diverse and inclusive workplace, and we embrace different styles of thinking. Maersk is an equal opportunities employer and welcomes applicants without regard to race, colour, gender, sex, age, religion, creed, national origin, ancestry, citizenship, marital status, sexual orientation, physical or mental disability, medical condition, pregnancy or parental leave, veteran status, gender identity, genetic information, or any other characteristic protected by applicable law. We will consider qualified applicants with criminal histories in a manner consistent with all legal requirements.
 <br/>
 <br/>
 We are happy to support your need for any adjustments during the application and hiring process. If you need special assistance or an accommodation to use our website, apply for a position, or to perform a job, please contact us by emailing accommodationrequests@maersk.com.
</div>


AI/ML Scientist(Operations research/Optimization/Simulation)

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