Postdoctoral Research Associate - Large-Scale Simulations for Additive Manufacturing

We need to produce HTML fragment with sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. We must not repeat job title. Must not include Job ID/requisition numbers as headings; can fold minor metadata into short

or drop it. Must preserve all substantive info; no invented or summarized away detail. Remove boilerplate: cookie/navigation/legal/EEO/equal-opportunity/scam-warning, duplicated lines, application instructions. Also remove instructions about uploading documents, etc. Must keep substantive info: overview, duties/responsibilities, basic qualifications, preferred qualifications, special requirements (export control, visa sponsorship, letters of recommendation, appointment length, etc.), about ORNL (benefits, etc). Also maybe mention pay? Not given. So we should not create Pay or Schedule sections unless stated. Benefits: there is a paragraph about ORNL offers competitive pay and benefits programs, listing many benefits. So we can include Benefits section with that list. Also maybe mention appointment length up to 24 months with potential extension; that could be under Requirements or maybe under a separate section like "Appointment Details". But we only have allowed headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We can map content: About the role: overview of position, division, group, mission. Responsibilities: major duties/responsibilities. Requirements: basic qualifications? Or maybe Requirements = basic qualifications. Qualifications: preferred qualifications. Skills: maybe expertise listed? Could combine. But we need to avoid thin sections. Let's think: We have substantive content for About the role, Responsibilities, Basic Qualifications, Preferred Qualifications, Special Requirements (export control, visa, letters, appointment length), Benefits (ORNL benefits). Also maybe "About ORNL" could be part of About the role or separate but we don't have a heading for that. Could include in About the role. We must not create Pay or Schedule sections because not stated. So we will output sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits. Possibly also "Special Requirements" could be under Requirements or Qualifications. But we have limited headings; we could incorporate special requirements into Requirements (like eligibility, export control, visa, letters). Or we could create a separate section but not allowed headings. So we fold into Requirements. Skills: maybe we can list specific technical skills: expertise in multi-physics simulations, FEM, ML, HPC, etc. That's from preferred qualifications. Could be under Skills. We must not repeat job title. Must not include Requisition Id as heading; we can drop it or put in a short p at top maybe but better to drop as minor metadata. We must preserve all substantive information; do not invent or summarize away detail. So we need to keep details like: PhD degree in mechanical engineering, material science, welding engineering or relevant engineering field with emphasis on computational modeling and simulations within past 5 years. Expertise in development and application of multi-physics simulations, digital twin, surrogate and reduced-order models and machine learning tools for part qualification and quantification of distortion, residual stress, microstructure and fatigue. Effective interpersonal skills, written and oral communication skills, strong motivation. Preferred qualifications: demonstrated expertise in multi-physics simulations using FEM for part qualification and quantification; demonstrated expertise in design and implementation of multi-physics codes for metal AM applications including thermo-mechanical response as well as microstructure and phase transformation response; demonstrated expertise in process development/optimization for digital twin, surrogate and reduced-order models and ML/AI tools applied to macro-scale deformation in AM; experience with multi-physics simulations on HPC and ML; experience working in a multi-disciplinary research environment. Special requirements: applicants cannot have received PhD more than five years prior to date of application and must complete all degree requirements before starting appointment. Appointment length up to 24 months with potential for extension. Initial appointments and extensions subject to performance and availability of funding. Export control, no clearance: position requires access to technology subject to export control requirements; successful candidates must be qualified for such access without an export control license. Visa sponsorship not available. Letters of recommendation: submit three letters. Benefits: ORNL offers competitive pay and benefits programs; list: medical and retirement plans, flexible work hours, on-site fitness, banking, cafeteria, 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, Employee Discounts. Also mention that ORNL is a DOE lab, 80-year legacy, over 7000 employees, etc. Could be in About the role. We must not include boilerplate like equal opportunity employer, etc. Remove those lines. We must not include application instructions like uploading documents, etc. We must not include lines about Real ID, PIV card, background check, etc? Those are substantive? They are about employment requirements; maybe they are part of Requirements? They are about eligibility for ORNL employment. The posting includes that info; we should preserve substantive information. However, the instruction says remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The Real ID, PIV card, background check are not exactly boilerplate; they are specific employment requirements. Might be considered part of Requirements. We'll include them under Requirements as part of eligibility. But we need to be careful not to include too much boilerplate. The lines about "For employment at Oak Ridge National Laboratory (ORNL), a Real ID compliant form of identification will be required..." etc. That's specific to ORNL; we can keep. We also need to keep the statement about the position remaining open for minimum 5 days etc. That's administrative; maybe we can drop as minor metadata? It's not a heading; could be a short p at end but maybe we drop as it's not substantive to role. The instruction says preserve ALL substantive information; does that include administrative details like opening period? Might be considered substantive but minor. However, they said "fold minor metadata into a short

or drop it." So we can drop or put in a short p. Probably drop. Now produce HTML. Structure:

About the role

... overview ...

Responsibilities

• ... each duty ...

Requirements

• ... basic qualifications ...
• ... special requirements ...

maybe separate lists. But we need to avoid mixing too much; we can have multiple

paragraphs. Better: Use

for prose,

• for lists. We'll produce:

  About the role

  We are seeking a Postdoctoral Research Associate for the development and application of advanced multiphysics simulations and machine learning (ML) methods relevant to additive manufacturing (AM), virtual manufacturing, material characterization, topology optimization, and real-time sensing. This position resides in the Computational Sciences and Engineering Division (CSED) at Oak Ridge National Laboratory (ORNL). CSED focuses on transdisciplinary computational science and analytics at scale to enable scientific discovery across the physical sciences, engineered systems, and biomedicine and health. It provides foundations and advances in quantum information sciences to enable quantum computers, devices, and networked systems. It develops community applications, data assets, and technologies and provides assurance to build knowledge and impact in novel, crosscut-science outcomes. The candidate will be a postdoctoral researcher within the Multiscale Materials (MsM) group of the Advanced Computing Methods for Physical Sciences Section in CSED. The MsM group is focused on delivering multiscale, multi-fidelity computational models and systems using algorithms and analytics for materials and related physical sciences for a broad range of energy, transportation, and advanced manufacturing applications. The MsM group also develops artificial intelligence (AI) and foundational ML models to accelerate multiscale materials and flow sciences.

  Responsibilities

  • Collaborate within a multi-disciplinary research environment consisting of computational scientists, computer scientists, experimentalists, and engineers/physicists conducting basic and applied research in support of the Laboratory’s missions.
  • Participate in the development of multi-physics simulations with machine learning (ML) methods for modeling and optimization of metallic materials and advanced manufacturing processes.
  • Participate in the design of integrated, scalable numerical methods and uncertainty quantification.
  • Follow team planning, documentation, verification and validation, and manufacturing-material-related simulation quality processes.
  • Author peer‑reviewed papers, technical papers, reports and proposals for internal and external release as well as represent the organization by giving technical presentations in large public forums.

  Requirements

  • PhD degree in mechanical engineering, material science, welding engineering or a relevant engineering field with emphasis on computational modeling and simulations obtained within the past 5 years.
  • Expertise in the development and application of multi‑physics simulations, digital twin, surrogate and reduced‑order models and machine learning tools for part qualification and quantification of distortion, residual stress, microstructure and fatigue.
  • Effective interpersonal skills, written and oral communication skills, and strong motivation.
  • Applicants must not have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting the appointment.
  • The appointment length is up to 24 months with the potential for extension, subject to performance and availability of funding.
  • This position requires access to technology subject to export control requirements; successful candidates must be qualified for such access without an export control license.
  • Visa sponsorship is not available for this position.
  • Three letters of recommendation must be submitted with the application.
  • For employment at ORNL, a Real ID‑compliant form of identification will be required; employees must obtain and maintain a federal Personal Identity Verification (PIV) card, which requires a favorable post‑employment background investigation including a declaration of illegal drug activities (including marijuana and cannabis derivatives) within the last year.

  Qualifications

  • Demonstrated expertise in multi‑physics simulations using Finite Element Methods (FEM) for part qualification and quantification.
  • Demonstrated expertise in design and implementation of multi‑physics codes for metal AM applications including thermo‑mechanical response as well as microstructure and phase‑transformation response.
  • Demonstrated expertise in process development/optimization for digital twin, surrogate and reduced‑order models and ML/AI tools applied to macro‑scale deformation in AM.
  • Experience with multi‑physics simulations on high performance computing (HPC) and ML.
  • Experience working in a multi‑disciplinary research environment.

  Skills

  The role requires strong skills in multi‑physics modeling, machine learning, high‑performance computing, and additive manufacturing processes, along with excellent communication and teamwork abilities.

  Benefits

  • Competitive pay and benefits programs.
  • Medical and retirement plans.
  • Flexible work hours.
  • On‑site fitness, banking, and cafeteria facilities.
  • 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, Rel