Post-Doctoral Fellow

Worcester Polytechnic Institute • Worcester, MA

12d • $45,000 - $70,000 • Onsite

About The Position

The Integrated Materials and Processes Design (IMPD) group at Worcester Polytechnic Institute (WPI) invites applications for a Postdoctoral Fellow position in computational materials science with a focus on advanced density functional theory (DFT), machine learning, and multiscale materials modeling for alloys and ceramics. The successful candidate will conduct cutting-edge research involving first-principles calculations mainly using VASP and related computational tools to investigate elevated-temperature phase stability, thermodynamic and mechanical properties, defect chemistry, diffusion behavior, and electrical/functional properties of structural and energy materials. The position also involves the integration of machine learning and AI-assisted approaches into materials modeling workflows. The postdoctoral researcher is expected to work independently, develop computational workflows and machine-learning models, contribute to proposal and manuscript preparation, and collaborate with graduate students and external research partners.

Requirements

• Ph.D. in Materials Science and Engineering, Physics, Chemistry, Mechanical Engineering, or a related field
• Strong expertise in density functional theory (DFT)
• Hands-on experience with VASP
• Experience with Linux/HPC environments and parallel computing
• Strong programming skills in Python or related scientific programming languages
• Experience in scientific data analysis and workflow automation
• Strong written and verbal communication skills

Nice To Haves

• Finite-temperature property calculations
• CALPHAD or thermodynamic modeling
• Defect calculations and diffusion modeling
• Mechanical property calculations from first principles
• Machine learning for materials science
• Development of AI/ML workflows and surrogate models
• High-throughput DFT calculations
• Experience with ML interatomic potentials
• Experience with materials databases and automated workflow frameworks
• Experience with alloys, ceramics, oxides, or energy materials

Responsibilities

• Perform advanced first-principles calculations primarily using VASP
• Conduct atomistic modeling of alloys, ceramics, and functional materials
• Develop computational workflows for high-throughput simulations
• Integrate machine learning methods with DFT-generated datasets
• Develop and maintain scientific codes/scripts in Python or related languages
• Analyze and interpret large-scale computational datasets
• Publish research results in high-impact peer-reviewed journals
• Assist in proposal preparation and collaborative research activities
• Mentor graduate and undergraduate students as needed

Benefits

• paid time off
• health insurance
• life and long-term disability insurance
• retirement savings plans
• tuition assistance
• flexible spending accounts

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree