Assistant Professor in Machine Learning, Biostatistics, and Bioinformatics

Colorado State University•Fort Collins, CO

39d•Onsite

About The Position

The Orthopaedic Research Center at Colorado State University seeks applicants for a 9-month Tenure-Track Assistant Professor position in Machine Learning, Biostatistics and Bioinformatics. The hire has the possibility of being named to the Abigail KawÄnanakoa Chair if suitably qualified. The ultimate decision for appointing an endowed Chair resides with the Dean of the College of Veterinary Medicine and Biomedical Sciences (CVMBS). The position will reside in the Department of Clinical Sciences within in the CVMBS and is in partnership with the Translational Medicine Institute. There is the possibility of having an affiliation with the School of Biomedical and Chemical Engineering in the Walter Scott College of Engineering. We invite applications from candidates specializing in artificial intelligence, digital engineering, statistical analysis, machine learning, or bioinformatics to advance interdisciplinary, translational research through externally funded collaborations with scientists, engineers, and veterinary clinician-scientists. Candidates seeking development or continuation of an independent research program in partnership with a dynamic team are sought. This position's mission and purpose would follow the aligned visions of all collaborative entities, those including but not limited to the Orthopaedic Research Center (ORC), the Translational Medicine Institute (TMI), the School of Biomedical Engineering (SBME), the College of Veterinary Medicine and Biomedical Sciences (CVMBS), and the Walter Scott Jr. College of Engineering - Department of Systems Engineering (WSCOE). Collaboration is a central component of our educational and research efforts at CSU, and with our partners around the world. Central pillars to all the aforementioned units' missions include the importance of improving the lives of animals, humans, and society through discovery, innovation, and education. As part of the focus on "translational" research that is both amenable to productization and to repurposing is encouraged. Opportunities for summer salary through research funding are also encouraged. Work authorization visa sponsorship may be available based on the specific situation for the selected final candidate. A signing bonus may be considered for successful candidates.

Requirements

PhD in Biomedical Engineering, Data Science, Biostatistics, Bioinformatics, Computational Biology, or a related field, completed by the time of hire

Nice To Haves

PhD completed
Successful candidates will demonstrate a strong commitment to research and teaching, with the potential to develop a strong record of external grant funding.
Expertise in biostatistics, machine learning, and multi-omics data integration particularly as they relate to imaging and biologic systems.
Strong programming skills (Python, R, MATLAB).
Experience with high-performance computing (cloud, local, and server) and large-scale imaging datasets.
Track record of peer-reviewed publications, conference proceedings, and collaborative research.
Grant writing experience with internal/external funding as a principal investigator.
Proven track record of strong collaboration, leadership, and mentorship across all levels, including, undergraduates, graduate students, post-doctoral students, and faculty.
Excellent communication and interdisciplinary collaboration skills.
Adept at harnessing data mining and machine learning approaches to address biological inquiries and facilitate the interpretation of high-dimensional data