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What are the key skills and qualifications needed to thrive as a Python PhD HPC (High Performance Computing) specialist, and why are they important?

To excel as a Python PhD HPC specialist, you need advanced knowledge of Python programming, parallel computing concepts, and a doctoral degree in a computationally intensive field. Familiarity with HPC clusters, job schedulers like SLURM, and libraries such as NumPy, SciPy, and MPI for Python is typically required. Strong analytical thinking, problem-solving, and collaboration skills set candidates apart in this role. These competencies ensure efficient development, optimization, and deployment of large-scale computational models that drive scientific research and innovation.

What are the typical challenges faced by a Python PhD HPC professional when working on large-scale computational projects?

Professionals in a Python PhD HPC role often encounter challenges related to optimizing Python code for high-performance computing environments, particularly when scaling computations across multiple nodes or clusters. Managing memory usage, debugging parallel code, and ensuring compatibility with various HPC libraries and frameworks are common hurdles. Additionally, effective collaboration with interdisciplinary teams—such as domain scientists, system administrators, and data engineers—is crucial for project success. Staying updated with advancements in both Python and HPC technologies also requires ongoing learning and adaptability.

What is a Python PhD HPC specialist?

A Python PhD HPC specialist is a professional with a doctoral degree who uses the Python programming language to develop and optimize high-performance computing (HPC) applications. These specialists often work on complex scientific or engineering problems that require significant computational resources, such as simulations, data analysis, or machine learning at scale. They possess deep expertise in both Python programming and HPC environments, including parallel computing, distributed systems, and cluster management. Their work often bridges the gap between theoretical research and practical implementation on supercomputers or large compute clusters.
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Infographic showing various Python Phd Hpc job openings in Mississippi as of July 2026, with employment types broken down into 1% As Needed, 91% Full Time, 6% Part Time, and 2% Contract. Highlights an 91% Physical, 4% Hybrid, and 5% Remote job distribution.

Research Scientist - National Center for Computational Hydroscience and Engineering (NCCHE)

University of Mississippi

Oxford, MS • On-site, Remote

Full-time

Posted 19 days ago

University Of Mississippi rating

7.9

Company rating: 7.9 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

205th of 614 rated colleges and universities

Job description

The University of Mississippi - fondly referred to as Ole Miss - stands as a premier public research institution with a proud legacy of academic distinction. We are devoted to nurturing a vibrant, inclusive community where every member - student, faculty, and staff - can achieve their fullest potential.

Job Summary:

This position focuses on developing and maintaining computational and geospatial technologies that support agricultural watershed science, water quality assessment, dam-break flood modeling, risk evaluation, and emergency planning. The role emphasizes building decision-support systems and web-based tools, managing large environmental datasets, and enabling data-driven environmental management through advanced modeling, software engineering, and GIS/remote sensing workflows.
It also includes supporting high-performance and Linux-based research computing environments, contributing to scientific communication (journal articles, technical reports, and conference presentations), and collaborating with interdisciplinary teams and stakeholders. In addition, the role supports grant proposal development and may include leading external research efforts.

Job Description:

Essential Duties/ Responsibilities:
  • Develop computational models, software tools, and web-based decision support systems for agricultural watershed processes, water quality assessment, dam-break flood modeling, risk assessment, and emergency planning.
  • Develop and maintain scientific software, geospatial applications, databases, and computational workflows using programming languages such as FORTRAN, C++, Python, R, and related technologies.
  • Design, develop, and maintain geospatial databases, web mapping applications, decision-support systems, and cloud- or cluster-based cyberinfrastructure to support environmental modeling, visualization, and data dissemination.
  • Manage and process large environmental and hydrologic datasets using GIS, remote sensing, spatial databases, and geospatial analysis tools.
  • Support high-performance computing, Linux-based research computing environments, automation workflows, and related computational infrastructure required for environmental modeling and data-intensive research.
  • Participate in and lead external research grant proposal development.
  • Participate in and lead peer-reviewed journal publications, technical reports, and scientific conference presentations.
  • Collaborate with interdisciplinary teams of scientists, engineers, and stakeholders to develop innovative solutions for water resources and environmental management challenges.

Job Responsibilities:

Preferred Experience, Knowledge, Skills & Abilities:
  • Experience in developing computational models, decision-support systems, and web-based tools for hydrologic, hydraulic, watershed, water quality, and environmental management.
  • Experience in scientific programming (e.g., FORTRAN, C++, Python, R), software development, computer systems, and computational infrastructure for environmental and geospatial applications..
  • Experience in geospatial analysis and environmental data management using GIS, remote sensing, spatial databases, and web-based geospatial technologies.
  • Experience with database design, administration, and optimization, including PostgreSQL/PostGIS and large-scale spatial data processing.
  • Experience in developing and deploying geospatial web services, map servers, and cloud- or cluster-based computing environments for environmental modeling and visualization.
  • Experience with Linux system administration, high-performance computing (HPC), virtualization, automation, and research computing infrastructure.
  • Excellent oral, written, and presentation skills (both technical and non-technical).
  • Experience in AIMS and/or DSS-WISE modeling and decision support systems is preferred.
Education:
  • Ph.D. in Computational Hydroscience and Engineering, or a closely related discipline. The PhD degree should be already received or about to be received at the end of the current semester.

* This position is fully or partially funded by external research grants. Continued employment is contingent upon satisfactory performance and the ongoing availability of funding.


** Applicants are requested to attach a Resume/CV with their application.

Education Qualifications:

PhD (Required)

Experience:

Interview Requirement:

Interview Requirements: Any candidate who is called for an interview must notify the Department of Equal Opportunity/Regulatory Compliance in writing of any reasonable accommodation needed prior to the date of the interview.

EEO Statement:

The University of Mississippi provides equal opportunity in any employment practice, education program, or education activity to all qualified persons. The University complies with all applicable laws regarding equal opportunity and does not unlawfully discriminate against any employee or applicant for employment based upon race, color, gender, sex, pregnancy, sexual orientation, gender identity or expression, religion, national origin, ethnicity, citizenship, age, disability, military status, protected veteran status, genetic information, or any other legally protected status.

Background Check Statement:

The University of Mississippi is committed to providing a safe campus community. UM conducts background investigations for applicants being considered for employment. Background investigations include a criminal history record check, and when appropriate, a financial (credit) report or driving history check.

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