Employment Opportunities

CNERG is frequently seeking additional group members at all levels to assist us in our mission of delivering new computing capability for the analysis of nuclear energy systems.

While each position will require specialized skills to fulfill that role, staff and students at all levels will be expected to be proficient with the basic tools of robust software development. We often refer to these skills collectively as Software Carpentry.

Graduate Student Opportunities

Specific opportunities, if any, are listed above. There may also be opportunities for exceptional students in the general areas identified below. All of these tasks will require programming and software development and students with demonstrated experience with Software Carpentry skills will be preferred. Prospective students are encouraged to apply for graduate study in our department and draw specific attention to these topics, indiciating what unique knowledge or experiences they will bring to these tasks.

PhD Topics

  • Hybrid Acceleration Schemes for Multi-physics Problems Driven by Monte Carlo Radiation Transport Work in this area will extend existing methodologies for accelerating Monte Carlo radiation transport for multi-physics problems, looking at a wider variety of other physics coupling and over different regions of phase space.

  • Shape Optimization for Radiation Transport This will explore algorithms for optimizing the shape of engineered systems to achieve specific performance goals. Such methods are widespread in other engineering disciplines but are not yet widely adopted for radiation transport problems.

  • Data Science Approaches for Nuclear Non-Proliferatin A growing set of data streams is available for use by various agencies for the detection of the misuse of nuclear material and nuclear facilities. This project will explore the use of novel algorithms and methodologies for the automated analysis of these data streams to support decision making.

  • Socioeconomic Metrics for Advanced Nuclear Fuel Cycles This will develop software algorithms to convert fundamental fuel cycle simulation results into quantities that are relevant for socioeconomic assessment of those fuel cycles.

Master’s Topics

  • Robust workflows for CAD-based Monte Carlo radiation transport This will require understanding of computational geometry, mesh generation, and manipulation of mesh to improve the robustness of analysis workflows to imperfections in the geometry or the geometry processing steps.

  • Generalized High Throughput Support for Monte Carlo Radiation Transport This project will develop scripts and tools to distribute Monte Carlo radiation transport calculations across a large set of loosely coupled computing resources, including: multi-job setup, multi-job control and monitoring, and multi-job aggregation. Target platforms will include UW-based HTCondor resources, Open Science Grid, and Amazon EC2. The tools will be implemented in PyNE for robustness and longevity.

Undergraduate Opportunities

CNERG is happy to provide opportunities for interested undergraduates to become involved in our computational research. As with most research groups, there are frequently tasks and assignments that are appropriate for an undergraduate who is just developing their research skills. The following paragraphs will hopefully give you an idea of what to expect if you were to join our CNERG community.

Many research groups will assign repetitive tasks to undergraduates that require minimal skills as a way for them to contribute and learn about the research. An overarching principle of our computational group is to automate repetitive tasks by writing software. A primary consequence of this is a relatively steep learning curve for new undergraduates who join the CNERG community, whether for the computational tools we use in our work or the software development skills we use to develop new capability.

When you join the CNERG team as an undergraduate, you will be assigned some exploratory tasks intended to improve the automation of our workflows and effectiveness of our researchers. You will probably be assigned to work closely with a graduate student who will be the primary mentor of your work. Ideally, you will be able to spend nearly 10 hours/week on this work in order to make adequate progress and avoid the inefficiency of context switching every time you return to this work. It may not be possible to offer you a private desk for this work.