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PhD positions in computational materials science University

Job in Lincoln, Lancaster County, Nebraska, 68501, USA
Listing for: Computational Chemistry List Home
Full Time position
Listed on 2026-07-15
Job specializations:
  • Research/Development
    Research Scientist, Postdoctoral Research Fellow
Salary/Wage Range or Industry Benchmark: 25000 - 35000 USD Yearly USD 25000.00 35000.00 YEAR
Job Description & How to Apply Below
Position: 26.07.09 PhD positions in computational materials science at the University

Position Overview

The research group led by Prof. Dr. Vitaly Alexandrov at the University of Nebraska‑Lincoln (UNL), USA, invites applications for multiple fully funded PhD student positions. The team focuses on interdisciplinary and highly collaborative research projects aimed at accelerating the discovery and understanding of materials for energy storage and conversion. Selected candidates will use advanced computational methods to investigate the atomistic and electronic origins of material behavior.

Research

Focus
  • Electrocatalysis
    :
    Evaluating the activity, selectivity, and structural stability of novel electrocatalysts.
  • Photoelectrocatalysis
    :
    Unraveling the complex interfacial chemistry, charge‑transfer dynamics, and reactivity of semiconductor‑liquid interfaces.
  • Complex Interfaces
    :
    Probing the fundamental structural and surface properties of complex‑oxide/liquid interfaces.
  • Low‑Dimensional Phenomena
    :
    Exploring the optoelectronic and magnetic properties of 2D materials and heterostructures.
Required Qualifications
  • Bachelor’s or Master’s degree in Chemistry, Physics, Materials Science, Chemical Engineering, or a closely related discipline.
  • Strong foundation in electronic structure theory, solid‑state physics, or theoretical/quantum chemistry.
  • Practical programming experience (preferably in Python) and familiarity with Linux environments and high‑performance computing (HPC) clusters.
  • Excellent problem‑solving abilities, strong communication skills, and the capacity to work both independently and collaboratively within a diverse, multidisciplinary team.
Preferred Qualifications
  • Prior experience with density functional theory (DFT), ab initio molecular dynamics (AIMD), or machine learning interatomic potentials (MLIPs).
  • Solid conceptual background in electrochemistry.
Contact

Interested candidates should send an e‑mail with their resume and representative publications to valexandrov2[]unl.edu (replace [] with @ before sending).

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