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Phase Field Postdoctoral Position Jobs (NOW HIRING)

Indiana University

Postdoctoral Fellow

Bloomington, IN · On-site

$45K - $61K/yr

Posting Details Position Details Title Postdoctoral Fellow Appointment Status Non-Tenure Track ... Research experience in one or more relevant areas, including lattice QCD, effective field theory ...

The Pennsylvania State University

$61K/yr

The person in this position will be in charge of setting up and overseeing experiments in the greenhouse and field, as well as manipulating insects in enclosures. The postdoc is expected to complete ...

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Phase Field Postdoctoral Position information

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$25K

$59K

$83.5K

How much do phase field postdoctoral position jobs pay per year?

As of Jun 7, 2026, the average yearly pay for phase field postdoctoral position in the United States is $59,022.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,000.00 and $66,500.00 per year, depending on experience, location, and employer.

What are some typical collaboration opportunities for a postdoc in a Phase Field research position?

As a Phase Field Postdoctoral researcher, you’ll frequently collaborate with interdisciplinary teams, including computational scientists, materials engineers, and experimentalists. These collaborations often involve joint meetings to discuss simulation results, refine models based on experimental data, and co-author academic papers. Such teamwork not only enhances the quality and impact of research but also helps you build a strong professional network, which is valuable for future career opportunities. Many institutions also encourage postdocs to mentor graduate or undergraduate students, further expanding your collaborative experience.

What are the key skills and qualifications needed to thrive as a Phase Field Postdoctoral Researcher, and why are they important?

To thrive as a Phase Field Postdoctoral Researcher, you need a PhD in materials science, physics, or a related field, with expertise in computational modeling and phase field theory. Proficiency in programming languages like Python or C++, simulation software such as MOOSE or FiPy, and experience with high-performance computing environments are typically required. Strong analytical thinking, problem-solving skills, and the ability to communicate complex findings clearly are essential soft skills. These skills enable researchers to develop accurate models, collaborate effectively, and advance scientific understanding in materials research.

What is the difference between Phase Field Postdoctoral Position vs Materials Science Postdoctoral Researcher?

AspectPhase Field Postdoctoral PositionMaterials Science Postdoctoral Researcher
Required CredentialsPhD in Materials Science, Physics, or related fieldPhD in Materials Science, Physics, or related field
Work EnvironmentResearch labs focusing on computational modeling and simulationsResearch labs with experimental and computational work in materials
Employer & Industry UsageUniversities, research institutes, industry R&DUniversities, research institutes, industry R&D
Common Search & ComparisonYesYes

The Phase Field Postdoctoral Position typically involves computational modeling of microstructure evolution using phase field methods, whereas the Materials Science Postdoctoral Researcher may focus on both experimental and computational studies in materials. Both roles require similar credentials and are found in academic, research, and industry settings, often searched together by candidates interested in advanced materials research.

What is a Phase Field Postdoctoral Position?

A Phase Field Postdoctoral Position is a research-focused role for individuals who have recently completed their Ph.D., typically in materials science, physics, or related fields. The work centers on using phase field modeling, a computational technique for simulating the evolution of microstructures in materials. Postdocs in this position develop and apply mathematical models and simulations to study phenomena such as solidification, phase transformations, and microstructural evolution. These roles often involve collaboration with experimentalists, writing scientific papers, and contributing to grant proposals. The experience gained is valuable for careers in academia, industry, or government research.
Infographic showing various Phase Field Postdoctoral Position job openings in the United States as of May 2026, with employment types broken down into 90% Full Time, and 10% Nights. Highlights an 91% Physical, 3% Hybrid, and 6% Remote job distribution, with an average salary of $59,022 per year, or $28.4 per hour.
Postdoctoral Appointee - Data Infrastructure and Software for AI

Postdoctoral Appointee - Data Infrastructure and Software for AI

Argonne National Laboratory

Lemont, IL • On-site

$70K - $117K/yr

Full-time

Posted 3 days ago

Job description

The Argonne Leadership Computing Facility's (ALCF) mission is to accelerate major scientific discoveries and engineering breakthroughs for humanity by designing and providing world-leading computing facilities in partnership with the computational science community. We help researchers solve some of the world's largest and most complex problems with our unique combination of supercomputing resources and computational science expertise.
The ALCF has an opening for a postdoctoral position in data management targeting AI applications at scale. The successful candidate will join the AL/ML group, a vibrant multidisciplinary team of scientists and High Performance Computing (HPC) engineers. In the AL/ML group, we work at the forefront of HPC to push scientific boundaries, carrying out research and development in state-of-the-art data management, machine learning and statistics techniques. With the advancement of Exascale systems and the variety of novel AI hardware designed to accelerate both training and inference, the ALCF is studying the application of these techniques to a variety of our science applications, including but not limited to: Computational Chemistry, Plasma Physics, High Energy Physics, analysis of Light Source data such as that from the Advanced Photon Source, Biology, Astronomy, and other science disciplines.
The chosen applicant will have a rare chance to work on exascale supercomputing systems and novel AI hardware to help solve significant real-world problems using machine learning and deep learning. ALCF researchers work in a highly collaborative environment involving science application teams, academia and industry, as well as other national labs and agencies, to solve some of the world's largest and most complex problems in science and engineering.
Objective:
  • The goal for this postdoctoral position to work on development and scaling of the data infrastructure and software for AI applications on supercomputing systems and AI testbed systems.
  • The postdoc will work on multimodal data management for science applications, focusing on integrating, organizing, and analyzing diverse data types to accelerate scientific discovery and innovation.
  • Another goal is to develop and evaluate vector databases and retrieval-augmented generation (RAG) and integrate agentic AI systems to meet the demands of large-scale fine-tuning and inference.
  • The postdoc will also work on design and implement agentic-AI workflows using the Model Context Protocol (MCP) to orchestrate data ingest and data movement across heterogeneous storage systems, including object stores.
  • The postdoc will also engage with science application teams and contribute to broader initiatives, including the American Science Cloud (AmSC) AI Services efforts, and to help us with design of future systems and data-management solutions to meet needs of our applications.

Benefit to ALCF:
This postdoc position will help ALCF evaluate and integrate data infrastructure needed to better facilitate AI models, including training, fine-tuning and inferencing, at scale. It will help us better understand and improve DAOS to meet the needs of AI-driven science applications. We expect the postdoc to help prototype, benchmark, and evaluate strategies to better support these workloads for Aurora.
Position Requirements
Required skills and qualifications:
  • A recent PhD (completed within the last 0-5 years) in computer science, computational science, a physical science, engineering, or related field
  • Comprehensive experience programming in one or more programming languages such as Python, C/C++
  • Experience with at least of one of the AI frameworks is required, such as PyTorch, TensorFlow
  • Ability to create, maintain, and support high-quality software is essential
  • Work with and contribute to domain-specific software and models
  • Experience with version control software such as git is essential
  • Effective written and oral communications skills
  • Ability to model Argonne's core values of impact, safety, respect, integrity and teamwork

Preferred skills and qualifications:
  • Experience with running simulations or AI workflows on supercomputers
  • Experience with training or applying large language models for research
  • Experience with MPI and Input/Output (I/O), and data management
  • Experience in writing technical papers and presentations

Job Family
Postdoctoral
Job Profile
Postdoctoral Appointee
Worker Type
Long-Term (Fixed Term)
Time Type
Full time
The expected hiring range for this position is $70,758.00-$117,925.00.
Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors such as, but not limited to, the scope and responsibilities of the position, the qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs. Additionally, comprehensive benefits are part of the total rewards package.
Click here to view Argonne employee benefits!
As an equal employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative scientific discovery and innovation. Argonne encourages everyone to apply for employment. Argonne is committed to nondiscrimination and considers all qualified applicants for employment without regard to any characteristic protected by law.
Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department.
All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis. Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.

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