Position Summary
This facilitation includes direct user support as well as broader participation in project development and research activities. The core duties and responsibilities in this role include:
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Engaging and collaborating with MSU and Henry Ford Health researchers who use (or plan to use) advanced computational resources in their research, including MSU’s High Performance Computing Center (HPCC), NSF ACCESS resources, high-throughput computing, and cloud computing.
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Collaborating with MSU and Henry Ford Health researchers to develop proposals, papers, public datasets, and open-source software to conduct and disseminate research. This may include extended collaborative support efforts as well as performing research.
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Developing, implementing, and refining training materials relating to research computing and research data through synchronous and asynchronous workshops, web-based tutorials, and documentation.
Research Computing Facilitators typically work with researchers both in person and remotely, and ICER works in a hybrid (partially in-person) work environment. While we anticipate that a successful applicant would start in Fall 2026, a later start date may be possible.
For consideration under this posting, a candidate must be a U.S. citizen.
As an institution of higher learning, Michigan State University is committed to providing a safe environment for its students, faculty, and staff in support of its educational mission. With this commitment, the University conducts criminal background checks and professional misconduct reviews of all applicants for employment in faculty, academic staff, and executive management searches.
Professional Misconduct Review
A professional misconduct review is a prerequisite for a candidate to be selected for this position. Applicants will be asked to disclose whether they are subject to any pending investigation, findings or sanctions related to professional misconduct. Professional misconduct includes misconduct related to a person’s employment, including, but not limited to, theft, embezzlement, research integrity, discrimination, or harassment under civil rights laws and policies, including protected identity harassment, sexual harassment, sexual misconduct (sexual assault, sexual exploitation, dating violence, domestic violence, stalking, etc.), and retaliation. All applicants will be asked to sign an authorization and release, which authorizes the University to contact the candidate’s current and former employers, for a period of 7 years prior to the date of application, related to any pending investigations, findings of responsibility and/or sanctions related to professional misconduct. Nothing will be sent to current or former employers unless the candidate reaches the semi-finalist stage.
The existence of professional misconduct history does not automatically exclude a candidate from employment. The University will assess the history, including any information provided by the candidate, in determining whether it is compatible with the position. The University may decline to hire a candidate based on the professional misconduct review. All records obtained from external employers will be kept in a secure location, separate from personnel files. If an applicant fails to sign the authorization and release, the application will be deemed incomplete and will be withdrawn.
Equal Employment Opportunity Statement
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, citizenship, age, disability or protected veteran status.
Required Degree
Doctorate -PhD in any field that included a significant research computing component.
Minimum Requirements
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Strong technical and problem-solving skills, including Linux command line experience and programming experience with a modern language such as R, Python, or C++.
Desired Qualifications
In addition to the required qualifications, it is desired that a successful applicant would have one or more of the following qualifications:
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Experience with creating and using virtual machines (with, e.g., VirtualBox or Parallels Desktop), software containers (with, e.g., Docker, Singularity, or a similar tool), and/or creating workflows using these tools.
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Experience using machine learning and/or artificial intelligence techniques to solve scientific problems (including, e.g., the use of common tools such as PyTorch, TensorFlow, Keras, scikit-learn, Hugging Face).
