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Postdoctoral Dft Jobs (NOW HIRING)

Ucf

Postdoctoral Scholar, Physics

Orlando, FL

Shyam Kattel at the University of Central Florida, has an immediate opening for a postdoctoral ... Expertise with DFT, GC-DFT, and machine learning methods. * Strong oral and written communication ...

Ucf

Post Doctoral Scholar, Physics

Orlando, FL

The Postdoctoral Associate's Responsibilities include but are not limited to: * Performing computational modeling using DFT, GC-DFT, MD (AIMD, classical force fields, MLIP force fields) * Developing ...

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How much do postdoctoral dft jobs pay per year?

As of Jul 17, 2026, the average yearly pay for postdoctoral dft 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 common challenges faced by postdoctoral researchers working in Density Functional Theory (DFT) positions?

Postdoctoral researchers specializing in Density Functional Theory (DFT) often encounter challenges such as keeping up with rapidly evolving computational methods, managing large-scale simulations, and interpreting complex data. Collaboration is key, as DFT postdocs frequently work with experimentalists and interdisciplinary teams to validate computational results. Balancing independent research with contributions to larger group projects can also be demanding but provides valuable experience for future academic or industry roles.

What are Postdoctoral DFT positions?

Postdoctoral DFT positions are research roles for individuals who have recently completed a PhD and are specializing in Density Functional Theory (DFT), a computational quantum mechanical modeling method used in physics, chemistry, and materials science. These positions typically involve advanced research on electronic structure calculations, materials design, or chemical simulations using DFT techniques. Postdoctoral researchers in this area work in academic, governmental, or industrial labs, contributing to scientific publications and collaborating with interdisciplinary teams.

What are the key skills and qualifications needed to thrive as a Postdoctoral DFT (Density Functional Theory) researcher, and why are they important?

To excel as a Postdoctoral DFT researcher, you need a strong background in computational chemistry or physics, experience with quantum mechanical modeling, and a PhD in a related field. Familiarity with DFT software packages like VASP, Quantum ESPRESSO, or Gaussian, along with proficiency in programming languages such as Python or Fortran, is typically required. Strong problem-solving abilities, effective communication, and collaborative skills set outstanding candidates apart in research environments. These competencies are crucial for conducting advanced simulations, interpreting results accurately, and contributing to impactful scientific advancements.
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Postdoctoral Dft jobs near you
Infographic showing various Postdoctoral Dft job openings in the United States as of July 2026, with employment types broken down into 97% Full Time, 1% Part Time, and 2% Contract. Highlights an 93% Physical, 5% Hybrid, and 2% Remote job distribution, with an average salary of $59,022 per year, or $28.4 per hour.
Postdoctoral Research Associate - Isayev Lab

Postdoctoral Research Associate - Isayev Lab

Carnegie Mellon University

Pittsburgh, PA • On-site

Full-time

Posted 18 days ago

Carnegie Mellon University rating

8.6

Company rating: 8.6 out of 10

Based on 24 frontline employees who took The Breakroom Quiz

56th of 555 rated colleges and universities

Job description

Description
The Isayev Lab at Carnegie Mellon University invites applications for a postdoctoral researcher to lead projects at the interface of computational chemistry, machine learning, reaction mechanism elucidation, and automated molecular discovery. The position is ideal for a candidate who wants to turn deep mechanistic understanding into predictive models and closed-loop discovery workflows.
Our lab develops and applies machine learning methods for computational chemistry, materials science, and molecular discovery, including transferable neural network potentials, generative molecular design, and experiment-automation workflows. The postdoc will work in a collaborative CMU environment spanning computational chemistry, AI, automated experimentation, polymer chemistry, and catalysis.
Research directions may include:
Developing automated DFT / ML workflows for mechanistic studies of photoredox, organometallic, and radical catalytic reactions.
Building predictive models that connect quantum-chemical descriptors, catalyst structure, substrate scope, selectivity, and reaction performance.
Applying AIMNet2 and related ML/QM methods to accelerate conformer search, reaction-path exploration, catalyst screening, and high-throughput mechanistic modeling.
Designing closed-loop computational-experimental campaigns for transition metal catalysis, polymer synthesis, and related catalytic transformations.
Creating reusable, open, well-documented software workflows for reaction data generation, curation, featurization, and model deployment.
Collaborating with experimental groups at CMU and external partners to convert mechanistic hypotheses into experimentally testable predictions.
Qualifications
Desired background:
Ph.D. in chemistry, chemical engineering, materials science, or a related field.
Strong experience in computational reaction mechanisms, especially DFT studies of organic, organometallic, photoredox, radical, or homogeneous catalytic systems.
Fluency with Python and modern scientific computing workflows; experience with Git, HPC clusters, SLURM, Gaussian, ORCA, Q-Chem, xTB, RDKit, ASE, or related tools is highly valued.
Interest in machine learning, statistical modeling, active learning, descriptor development, or data-driven reaction prediction.
Ability to work closely with experimental collaborators and communicate mechanistic insight clearly.
Application Instructions
Applications, including a cover letter and a curriculum vitae indicating your interest and relevant training should be submitted electronically via Interfolio.

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