Postdoctoral Researcher: Subsurface Hydrology & Energy

Los Alamos National Laboratory

Los Alamos (NM)

On-site

USD 85,000 - 110,000

Full time

3 days ago
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Benefits offered by this job

Relocation packages
Onsite gym
Tuition assistance
Paid parental leave

Job summary

Los Alamos National Laboratory’s CHESS team seeks outstanding postdoctoral candidates in computational subsurface hydrogeology in Los Alamos, NM. You will advance high-fidelity models for carbon storage, geothermal energy, and nuclear waste disposal, and publish in peer‑reviewed journals.

Work will bridge subsurface flow, reactive geochemistry, and machine learning, with collaborations across disciplines and opportunities for national‑level recognition through fellowships and leadership in

Qualifications

  • PhD in a related field; within 5 years of completion.
  • Strong background in computational subsurface flow and transport modeling.
  • Proficiency in Fortran, C++, Python or Julia.
  • Experience with high-performance computing and research software engineering (git, CI).
  • Excellent written and oral English communication.

Responsibilities

  • Develop and apply DFN modeling using dfnWorks.
  • Simulate coupled THMC processes in subsurface systems.
  • Work with FEHM for single- and multiphase flow.
  • Publish results in peer‑reviewed journals and present at conferences.
  • Collaborate in a multidisciplinary team to advance subsurface energy science.

Skills

DFN modeling
THMC simulation
Numerical analysis
Fortran/C++/Python
HPC/CI
Publication potential
English communication

Education

PhD in Computational Hydrology/related field

Tools

dfnWorks
FEHM
ParaView/VisIt
MPI/GPU computing

Job description

Los Alamos National Laboratory’s CHESS team seeks outstanding postdoctoral candidates in computational subsurface hydrogeology in Los Alamos, NM. You will advance high-fidelity models for carbon storage, geothermal energy, and nuclear waste disposal, and publish in peer‑reviewed journals.

Work will bridge subsurface flow, reactive geochemistry, and machine learning, with collaborations across disciplines and opportunities for national‑level recognition through fellowships and leadership in

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