Requisition Id 16218 Overview: The Multiscale Biomedical Systems Group within the Advanced Computing in Health (ACH) section of the Computational Sciences and Engineering Division (CSED) at Oak Ridge National Laboratory (ORNL) seeks a motivated Research Professional. This position primarily focuses on large-scale molecular dynamics (MD) simulations and AI-integrated multiscale modeling of complex biosystems. The successful candidate will also contribute to efforts that bridge molecular, cellular, and systems-level modeling, with growing relevance to emerging paradigms such as whole-cell modeling and networked biological systems. You will work at the intersection of high-performance computing (HPC), computational biophysics, and machine learning, leveraging leadership-class computing resources and collaborating across ORNL, federal agencies, and academic partners. Key Responsibilities: <ul> <li style="font-family:arial, helvetica, sans-serif;font-size:10.0pt">Develop and apply scalable molecular dynamics (MD) and multiscale simulation workflows for biomolecular systems (proteins, enzymes, membranes, and complexes)</li> <li style="font-family:arial, helvetica, sans-serif;font-size:10.0pt">Integrate AI/ML approaches with physics-based simulations to accelerate discovery and improve predictive fidelity</li> <li style="font-family:arial, helvetica, sans-serif;font-size:10.0pt">Contribute to cross-scale modeling frameworks linking molecular interactions to cellular and network-level behavior (e.g. protein-protein interaction, PPI, network analysis)</li> <li style="font-family:arial, helvetica, sans-serif;font-size:10.0pt">Optimize simulation codes and workflows for leadership-class HPC architectures</li> <li style="font-family:arial, helvetica, sans-serif;font-size:10.0pt">Collaborate across interdisciplinary teams spanning biology, chemistry, computer science, and applied mathematics</li> <li style="font-family:arial, helvetica, sans-serif;font-size:10.0pt">Publish findings in high-impact journals and present at leading conferences</li> </ul> Required Qualifications: <ul> <li style="font-family:arial, helvetica, sans-serif;font-size:10.0pt">Ph.D. (within 0–5 years) in computational bioscience, computational biophysics, computer science, or a related field</li> <li style="font-family:arial, helvetica, sans-serif;font-size:10.0pt">Strong programming skills in C++, Python, or similar scientific computing languages</li> <li style="font-family:arial, helvetica, sans-serif;font-size:10.0pt">Extensive experience with MD simulation tools such as NAMD, GROMACS, AMBER, or LAMMPS, and visualization tools (e.g., VMD, PyMOL)</li> <li style="font-family:arial, helvetica, sans-serif;font-size:10.0pt">Experience working on high-performance computing (HPC) systems</li> <li style="font-family:arial, helvetica, sans-serif;font-size:10.0pt">Demonstrated ability to conduct independent research with a strong publication record</li> <li style="font-family:arial, helvetica, sans-serif;font-size:10.0pt">Demonstrated ability to obtain research funding (DoE, DoD, NIH, NSF etc)</li> <li style="font-family:arial, helvetica, sans-serif;font-size:10.0pt">Excellent written and verbal communication skills for interdisciplinary collaboration</li> <li style="font-family:arial, helvetica, sans-serif;font-size:10.0pt">Commitment to ORNL’s core values: Impact, Integrity, Teamwork, Safety, and Service</li> </ul> Preferred Qualifications: <ul type="disc"> <li style="font-family:arial, helvetica, sans-serif;font-size:10.0pt">Deep expertise in atomistic and multiscale simulation methods (e.g., MD, enhanced sampling, QM/MM)</li> <li style="font-family:arial, helvetica, sans-serif;font-size:10.0pt">Experience improving performance and scalability of simulation workflows via:</li> <ul type="circle"> <li style="font-family:arial, helvetica, sans-serif;font-size:10.0pt">Parallelization and performance engineering</li> <li style="font-family:arial, helvetica, sans-serif;font-size:10.0pt">GPU/accelerator optimization</li> <li style="font-family:arial, helvetica, sans-serif;font-size:10.0pt">Algorithmic innovation</li> </ul> <li style="font-family:arial, helvetica, sans-serif;font-size:10.0pt">Experience applying machine learning or AI to molecular simulation, including:</li> <ul type="circle"> <li style="font-family:arial, helvetica, sans-serif;font-size:10.0pt">Surrogate models or learned potentials</li> <li style="font-family:arial, helvetica, sans-serif;font-size:10.0pt">Generative models for biomolecular design</li> <li style="font-family:arial, helvetica, sans-serif;font-size:10.0pt">Representation learning for biomolecular systems</li> </ul> <li style="font-family:arial, helvetica, sans-serif;font-size:10.0pt">Familiarity with protein–protein interaction (PPI) networks, signaling pathways, or systems biology models (experience of bioinformatics tools)</li> <li style="font-family:arial, helvetica, sans-serif;font-size:10.0pt">Experience with integrated multiscale modeling frameworks connecting molecular dynamics to cellular or tissue-scale processes</li> <li style="font-family:arial, helvetica, sans-serif;font-size:10.0pt">Experience with deep learning frameworks such as PyTorch or TensorFlow</li> <li style="font-family:arial, helvetica, sans-serif;font-size:10.0pt">Exposure to AI-enabled scientific workflows that couple simulation with data-driven modeling, including emerging approaches involving foundation models or scientific LLMs</li> </ul> Special Requirements: This position requires the ability to obtain and maintain a clearance from the Department of Energy. As such, this position is a Workplace Substance Abuse (WSAP) testing designated position. WSAP positions require passing a pre-placement drug test and participation in an ongoing random drug testing program. About ORNL: As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation’s most pressing challenges. Our team is made up of over 7,000 dedicated and innovative individuals! Our goal is to create an environment where a variety of perspectives and backgrounds are valued, ensuring ORNL is known as a top choice for employment. These principles are essential for supporting our broader mission to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security challenges facing the nation. ORNL offers competitive pay and benefits programs to attract and retain individuals who demonstrate exceptional work behaviors. The laboratory provides a range of employee benefits, including medical and retirement plans and flexible work hours, to support the well-being of you and your family. Employee amenities such as on-site fitness, banking, and cafeteria facilities are also available for added convenience. Other benefits include the following: Prescription Drug Plan, Dental Plan, Vision Plan, 401(k) Retirement Plan, Contributory Pension Plan, Life Insurance, Disability Benefits, Generous Vacation and Holidays, Parental Leave, Legal Insurance with Identity Theft Protection, Employee Assistance Plan, Flexible Spending Accounts, Health Savings Accounts, Wellness Programs, Educational Assistance, Relocation Assistance, and Employee Discounts. If you have difficulty using the online application system or need an accommodation to apply due to a disability, please email: [email protected]This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired. We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment. ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply. UT-Battelle is an E-Verify employer.

Research Associate, Atomistic Simulations & AI-Driven Molecular Modeling (Oak Ridge, TN, US, 37830) @ Oak Ridge National Laboratory

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