Applications are invited for a Visiting Assistant Professor position in Actuarial Statistics at the Department of Statistics and Applied Probability at University of California Santa Barbara. The position is particularly suitable for graduating or recent biostatistics PhDs or applied statistics PhDs interested in working with medical and insurance data.
To be eligible, candidates should obtain their PhD by summer 2017. The successful candidates are expected to teach 2 quarter courses per year, to collaborate in research with faculty at the department and local medical community, and to supervise undergraduate and graduate research projects in the areas of predictive analytics for healthcare costs and time-series analysis of insurance data. For more information about the Department please see http://www.pstat.ucsb.edu/employment.htm#about
The position starts on September 1, 2017 and is for one year with possibility of renewal for a second year based on satisfactory review. Interested candidates should apply electronically via the UC Recruit website https://recruit.ap.ucsb.edu/apply/JPF00890 by submitting a resume, research and teaching statements, and arranging for three letters of reference (at least one letter should describe teaching accomplishments). Applications are continually reviewed until the position is filled. Note that this search is in addition to the regular Visiting Assistant Professor opening which covers other research areas in Statistics broadly defined, and is also ongoing. Further enquiries can be addressed to Este enderezo de correo está a ser protexido dos robots de correo lixo. Precisa activar o JavaScript para velo.
The Department is especially interested in candidates who can contribute to the diversity and excellence of the academic community through research, teaching and service. The University of California is an Equal Opportunity/Affirmative Action Employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law.
