Open date: July 1st, 2020
Last review date: Friday, Jul 31, 2020 at 11:59pm (Pacific Time)
Applications received after this date will be reviewed by the search committee if the position has not yet been filled.
Final date: Saturday, Jan 1, 2022 at 11:59pm (Pacific Time)
Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled.
Assistant Adjunct Professor - Department of Neurological Surgery
The UCSF Department of Neurological Surgery is seeking an expert in data science applied to neurotrauma for a full-time faculty position at the Brain and Spinal Injury Center (BASIC). The selected candidate will be appointed at the level of Assistant in the Adjunct Professor series (non-tenure track).
Faculty in the Adjunct Professor series are individuals who are predominately engaged in research or other creative work and who participate in teaching or individuals who contribute primarily to teaching and have a limited responsibility for research or other creative work; these individuals may be professional practitioners of appropriate distinction. The selected candidate will be expected to conduct research work involving the development and advancement of the application of data science approaches to solve neurotrauma research questions.
The successful candidate is expected to integrate within the existent research programs at the department providing expertise in data related matters to our neurotrauma research community. Specific research areas of interest include neurotrauma data integration, deep data curation applying specific spinal cord injury (SCI) and/or traumatic brain injury (TBI) domain knowledge, application of machine learning, use of electronic medical records for neurotrauma research, statistical modeling and inference, and data sharing, all in the context of neurotrauma (TBI/SCI). The ideal candidate will have a demonstrated track record of collaborating with both clinicians and basic scientists in multidisciplinary, and team-based translational research studies in both Spinal Cord Injury and Traumatic Brain Injury research. In addition, the candidate is expected to engage in providing help and training to other members of the department on matters related to data management, statistical planning and analysis, and reproducibility research in both animal models and human clinical studies. The candidate will integrate into existing data teams on the Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) and in Spinal Cord Injury (TRACK-SCI). As an independent investigator, the candidate will: (1) design and perform data-intensive and computational experiments; (2) develop and implement new analytic workflows; (3) analyze neurotrauma data; (4) provide scientific oversight of the projects including review and advice on experimental design, data interpretation, and long-term planning to her or his team and colleagues; (5) write manuscripts for publication in peer-review journals; and (6) pursue independent funding.
• PhD in spinal cord injury research or similar areas of study.
• Demonstrated knowledge in data and statistical methodologies.
• Knowledge and skills in experimental animal models as well as clinical neurotrauma research data.
• Strong statistical programming skills.
• Skills applying multivariate statistics to solve neurotrauma research questions.
• A minimum of five years of post-PhD work experience.
• Demonstrated involvement in collaborative team science research covering aspects of basic, clinical and translational research.
• A strong research record as an independent investigator is essential. This includes evidence of publishing in relevant peer-reviewed journals in the field and demonstrated capacity to secure external grant funding.
• Applicants should have experience teaching, mentoring, and advising trainees.
• Applicants should have demonstrated involvement on services to the research community.
• Statistical programming skills, preferably in the R programming language.
UC San Francisco seeks candidates whose experience, teaching, research, or community service that has prepared them to contribute to our commitment to diversity and excellence. The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age or protected veteran status.
Please apply online at https://aprecruit.ucsf.edu/JPF03015.
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