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About This Role
- 45002568
- 907 Floyd Avenue, VCU Main Campus, Virginia, United States, 23284
- VP Academic Affairs SML
- Research
- Full-Time (Salaried)
- Virginia Commonwealth University
The department of Mechanical and Nuclear Engineering within the VCU College of Engineering is seeking a Research Scientist in Computational Nuclear Engineering to support and advance research in computational modeling and simulation for nuclear science and engineering applications. The successful candidate will contribute to ongoing research programs involving advanced computational methods, reactor physics and multiphysics modeling, nuclear system design and analysis, and applications related to isotope production and isotope science.
Since its inception in 1996, the Virginia Commonwealth University College of Engineering has brought innovative, real-world engineering education to Central Virginia. Comprised of five different departments plus the Dean’s office, the College of Engineering enrolls more than 2,000 undergraduate and 500 graduate students in several degree programs supported by more than 650 full-time, part-time, and student employees. As part of a premier research university known for tenacity, love of the city of Richmond, and commitment to respect and access, the College of Engineering values the significant and positive impact of our people and ideas in the promotion of regional and global prosperity involving research and life sciences.
Duties & Responsibilities:
The position will support the research and educational objectives of a federally funded program focused on developing improved approaches for the efficient production of isotopes of interest and educating and training students to meet the growing workforce needs of the isotope R&D and production community. The Research Scientist will work closely with faculty, graduate students, undergraduate researchers, and external collaborators and will be expected to contribute both technical expertise and research leadership to the group.
The primary responsibilities of this position include:
- Computational Research and Method Development: Conduct and support computational research in nuclear science and engineering, including the development, implementation, verification, and application of advanced modeling and simulation methods for nuclear systems, with particular emphasis on applications supporting isotope production, isotope science, and related nuclear technologies.
- Collaborative Research: Partner with faculty, graduate students, undergraduate researchers, and external collaborators in the execution of existing research initiatives by providing expertise in computational nuclear system design, numerical modeling, simulation, data analysis, and interpretation of computational results.
- Development of New Research Directions: Assist in identifying, evaluating, and developing new research opportunities aligned with the group's expertise, from literature review, initial concept development and feasibility studies through proposal preparation and project execution.
- External Research Funding: Actively participate in the development of externally funded research proposals to federal agencies and other sponsors. The successful candidate will be highly encouraged to develop independent and collaborative research ideas and, when appropriate and consistent with University and sponsor policies, serve as Principal Investigator or Co-Principal Investigator in collaboration with faculty and other researchers.
- Research Documentation and Communication: Document computational methodologies, models, software, data, and research findings and communicate results effectively to faculty, students, project sponsors, external collaborators, and other stakeholders through technical reports, presentations, and project meetings.
- Scholarly Dissemination: Lead and contribute to the preparation of peer-reviewed journal articles, conference papers, technical reports, and presentations at established national and international conferences in nuclear science and engineering.
- Student Mentoring and Workforce Development: Provide technical guidance and day-to-day research mentoring to undergraduate and graduate students involved in computational nuclear engineering and isotope-related research. Contribute to the education and training of students in computational tools, modeling methodologies, research practices, and scientific communication relevant to careers in the nuclear and isotope R&D communities.
- Project Execution: Work effectively in a collaborative, multidisciplinary, and time-sensitive research environment and contribute to the timely completion of project milestones, deliverables, sponsor requirements, and research objectives.
Qualifications:
Minimum Qualifications
- Ph.D. in nuclear engineering, or a related discipline, or equivalent work experience that equates to a Ph.D.
- Have some full-time research or professional experience in computational nuclear engineering or closely related areas
- Demonstrated experience with one or more nuclear analysis codes such as MCNP, OpenMC, SCALE, etc.
- Demonstrated ability to publish research findings in peer-reviewed scientific or engineering journals and present research at established technical or scientific conferences
- Demonstrated ability to work in and foster an environment of respect, professionalism and civility with a population of faculty, staff, and students from all backgrounds and experiences, or a commitment to do so as a staff member at VCU.
Preferred Qualifications
- Advanced computational expertise in reactor physics, radiation transport, multiphysics modeling, isotope production, or related nuclear applications
- Scientific programming and high-performance computing experience, including proficiency with languages such as Python, C/C++, or Fortran
- Strong research productivity, demonstrated through peer-reviewed publications, conference presentations, and other significant scholarly contributions
- Experience in research development and leadership, including proposal preparation, externally funded research, student mentoring, or coordination of collaborative research activities
Salary Range: $80,000 - $90,000
Benefits: All full-time university staff are eligible for VCU’s robust benefits package that includes comprehensive health benefits, paid annual and holiday leave, generous tuition benefits, retirement planning and savings options, tax-deferred annuity and cash match programs, employee discounts, well-being resources, abundant opportunities for career development and advancement, and more.
FLSA Exemption Status: Non-Exempt
Hours per Week: 40
Restricted Position: Yes
ORP Eligible: Yes
Flexible Work Arrangement: Fully Onsite
University Job Title: 3324B - Scientist RS Base
Unit: College Of Engineering MBU
Department: Mechanical and Nuclear Engineering
Contact Information:
Contact Name: Sierra Cloud
Contact Email: [email protected]
Salary Context
This $80K-$90K range is in the lower quartile for Research Scientist roles in our dataset (median: $197K across 73 roles with salary data).
Role Details
About This Role
Research Scientists push the boundaries of what AI can do. They design experiments, develop novel architectures, publish papers, and translate research breakthroughs into production capabilities. This is where the fundamental advances happen, from attention mechanisms to diffusion models to reasoning chains.
The work is intellectually demanding and often ambiguous. You might spend months on an approach that doesn't pan out. The best research scientists combine deep mathematical intuition with engineering pragmatism. They know when to go deep on theory and when to run experiments. They read papers voraciously and can spot incremental contributions from genuine breakthroughs.
Across the 8,943 AI roles we're tracking, Research Scientist positions make up 2% of the market. At Virginia Commonwealth University, this role fits into their broader AI and engineering organization.
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
What the Work Looks Like
A typical week includes: reading and discussing recent papers with your team, designing and running experiments on multi-GPU clusters, analyzing results and iterating on hypotheses, writing up findings for internal review or publication, and collaborating with engineering teams to productionize promising results. The ratio of thinking to coding is higher than in engineering roles.
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
Skills Required
PhD strongly preferred for most roles. Deep expertise in a specific area (NLP, computer vision, reinforcement learning, multimodal) is expected. PyTorch is the standard. Publication track record matters. Strong mathematical foundations in linear algebra, probability, optimization, and information theory are assumed.
Beyond the fundamentals, companies value experience with large-scale distributed training, novel architecture design, and the ability to bridge theory and practice. Understanding of current frontier topics (reasoning, multimodal, long-context, alignment) is essential. Code quality matters more than many researchers expect. Labs want researchers who can implement their ideas cleanly.
Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.
Compensation Benchmarks
Research Scientist roles pay a median of $222,200 based on 708 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($85K) sits 62% below the category median. Disclosed range: $80K to $90K.
Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,250; VP: $235,000.
Virginia Commonwealth University AI Hiring
Virginia Commonwealth University has 3 open AI roles right now. They're hiring across Research Scientist, AI/ML Engineer. Based in VA, US. Compensation range: $90K - $150K.
Location Context
Across all AI roles, 6% (521 positions) offer remote work, while 8,351 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,416 roles, $263,811 median); Los Angeles (1,340 roles, $210,000 median).
Career Path
Common paths into Research Scientist roles include PhD Student, Research Engineer, Postdoc.
From here, career progression typically leads toward Research Lead, Distinguished Scientist, VP of Research.
The PhD is the entry point for most paths. Choose your advisor and research area carefully since they'll define your first industry position. Publish consistently, contribute to open-source projects in your area, and build relationships at conferences. Industry research offers better compensation and compute resources than academia, but the pressure to show product impact is real.
What to Expect in Interviews
Research interviews are multi-stage: a research talk (present your best paper), technical deep-dives on your methodology, and often a 'research proposal' exercise where you design an experiment to test a hypothesis. Coding rounds test implementation ability alongside theoretical knowledge. Be prepared to implement a paper from scratch and discuss the design choices the authors made. Strong candidates can critique papers constructively and identify gaps in experimental methodology.
When evaluating opportunities: Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.
AI Hiring Overview
The AI job market has 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.
The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 roles).
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
The AI Job Market Today
The AI job market spans 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (175) are outnumbered by mid-level (4,132) and senior (3,268) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,368 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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