ZipRecruiter

Log In

1

Polymer Postdoc Jobs (NOW HIRING)

LSU AgCenter

Postdoctoral Researcher

Patrick, SC · On-site

Postdoctoral Researcher Position Type:Other Academic Department:LSUAM Engineering - Chemical ... Perform research on polymer upcycling to liquid, gas, and solid products. Job Responsibilities: 50 ...

LSU AgCenter

Postdoctoral Researcher

Argonne, WI · On-site

They will collaborate with experts in polymer and ligand design, membrane fabrication and ... The postdoc will work closely with LSU faculty and will be embedded within the research environment ...

previous page

Showing results 41-60

All JobsPolymer Postdoc Jobs

Polymer Postdoc information

See salary details

$25K

$59K

$83.5K

How much do polymer postdoc jobs pay per year?

As of Sep 2, 2026, the average yearly pay for polymer postdoc 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 is a polymer postdoc?

A Polymer Postdoc is a research position for individuals who have earned a Ph.D. in polymer science, chemistry, materials science, or a related field. It typically involves conducting advanced research on polymer materials, synthesis, characterization, and applications in areas like healthcare, energy, or sustainability. Responsibilities may include designing experiments, publishing research, and collaborating with academic or industry partners. Postdocs gain hands-on experience and develop expertise to prepare for careers in academia, industry, or government research. The position is usually funded for a fixed term, often 1-3 years.

What does a polymer postdoc do?

A typical day for a Polymer Postdoc involves designing and conducting experiments related to polymer synthesis or characterization, analyzing data, and troubleshooting experimental setups. You will frequently collaborate with other researchers, graduate students, and sometimes industry partners on joint projects. Preparation of research manuscripts, grant proposals, and conference presentations also forms part of the weekly routine. This role offers a dynamic mix of hands-on lab work and critical thinking, often in a supportive research group or departmental environment.

What are the key skills and qualifications needed to thrive as a polymer postdoc?

To thrive as a Polymer Postdoc, you need a Ph.D. in polymer science, chemistry, materials science, or a related field, along with a strong background in polymer synthesis, characterization, and data analysis. Familiarity with advanced laboratory instrumentation (e.g., NMR, GPC, DSC), computational modeling tools, and safety protocols is highly beneficial. Excellent problem-solving abilities, scientific communication skills, and the ability to collaborate in interdisciplinary teams are important soft skills. These competencies are crucial for executing high-quality research, publishing results, and contributing effectively to academic or industrial projects.

More about Polymer Postdoc jobs

What cities are hiring for Polymer Postdoc jobs?

Cities with the most Polymer Postdoc job openings:

What are the most commonly searched types of Polymer Postdoc jobs?

The most popular types of Polymer Postdoc jobs are:

What states have the most Polymer Postdoc jobs?

States with the most job openings for Polymer Postdoc jobs include:

What job categories do people searching Polymer Postdoc jobs look for?

The top searched job categories for Polymer Postdoc jobs are:

Polymer Postdoc jobs near you
Infographic showing various Polymer Postdoc job openings in the United States as of August 2026, with employment types broken down into 87% Full Time, 9% Part Time, 1% Contract, and 3% Nights. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $59,022 per year, or $28.4 per hour.

Postdoctoral Appointee - Materials Informatics and Autonomous Synthesis

Argonne National Laboratory

Lemont, IL • On-site

$72K - $121K/yr

Full-time

Re-posted 13 days ago

Job description

The Center for Nanoscale Materials (CNM) at Argonne National Laboratory invites applications for a postdoctoral research position focused on developing AI/ML methods for autonomous materials discovery and synthesis.
We are seeking a creative and collaborative researcher who is excited by the opportunity to help shape the future of autonomous synthesis and self-driving laboratories. This role is ideal for someone who enjoys working at the intersection of data science, machine learning, materials research, and experiment, and who is motivated to translate computational advances into real laboratory workflows.
The position will focus on building the data resources, predictive models, and closed-loop decision frameworks needed to accelerate experimentation and advance next-generation autonomous laboratories. The broader goal is to enable AI-driven materials discovery, autonomous synthesis, and the development of high-quality, reusable datasets that support adaptive experimentation and long-term scientific impact.
This research may include applications in areas such as organic electrochemical and neuromorphic devices, but the central emphasis is on creating data-driven methods and infrastructure that can guide experiments, improve efficiency, and strengthen collaboration between computation and experiment.
Key Responsibilities
  • Develop machine learning-ready data resources for materials by integrating literature, in-house, and newly generated experimental data
  • Build surrogate and predictive models that connect composition, molecular structure, synthesis and processing conditions, morphology, and device-relevant properties
  • Design active learning, Bayesian optimization, uncertainty-aware modeling, and other adaptive experimental design workflows to guide experiments and improve data efficiency in autonomous platforms such as the Polybot
  • Work closely with experimental researchers to integrate AI/ML workflows into closed-loop autonomous synthesis, fabrication, and characterization; translate model predictions into experimental campaigns; and update models using newly acquired data
  • Contribute to strategies for generating diverse, high-value datasets, identifying meaningful descriptors and representations, and building reproducible computational pipelines, workflow automation, and data infrastructure that support long-term autonomous laboratory capabilities
  • Share research outcomes through publications, presentations, software, datasets, and internal reports

Position Requirements
  • Recent or soon-to-be-completed PhD (within the last 0-5 years) in chemistry, chemical engineering, materials science, polymer science, physics, computer science, and/or data science
  • Demonstrated accomplishments in materials informatics, scientific machine learning, or AI-guided experimental design
  • Strong Python and scientific computing skills, including experience with tools such as NumPy, pandas, scikit-learn, and machine learning frameworks such as PyTorch, TensorFlow, or similar
  • Experience developing surrogate models, predictive models, or adaptive learning workflows for scientific or engineering applications
  • Strong interest in working closely with experimental researchers in a laboratory-centered environment
  • Evidence of independent research productivity through publications, software, datasets, or similar outputs
  • Excellent communication skills, the ability to work effectively in interdisciplinary teams
  • Ability to model Argonne's core values of impact, safety, respect, integrity, and teamwork

Preferred Qualifications
  • Experience with active learning, Bayesian optimization, adaptive experimental design, reinforcement learning for experiments, or uncertainty quantification
  • Experience with autonomous, self-driving, or robotic laboratory platforms
  • Background in electronic polymers, conjugated polymers, organic semiconductors, soft materials, electrochemical materials, or related functional materials
  • Experience integrating literature, experimental, and simulation datasets into unified, machine learning-ready workflows
  • Familiarity with cheminformatics or polymer informatics, molecular representations, descriptor engineering, RDKit, characterization-informed modeling, multimodal data fusion, interpretable machine learning, NLP, text mining, or automated extraction of materials data from the literature
  • Experience with workflow automation, data infrastructure, database development, reproducible research pipelines, and collaborative environments that span computation, data science, and experiment

Application Materials
  • Updated CV/Resume
  • Unofficial Ph.D. transcripts
  • If already awarded, a copy of the Ph.D. diploma

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 $72,879.00-$121,465.00.
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.

Apply