Tenure Track Faculty Position at the University of Hawaii
The Department of Electrical Engineering seeks applications in the areas of statistical learning, big data, and related topics. Strong candidates in other areas are encouraged to apply as well.
Jan 19, 2018

The Department of Electrical Engineering seeks applications in the areas of statistical learning, big data, and related topics. 

This call is for a range of research from machine learning and statistics to big data, and information theory applied to data and statistical signal processing. Both theoretical and applied research are of interest, and successful candidates must be able to leverage their research to collaborate with other faculty on campus, as well as to develop an independent, competitively funded research program. 

NSF has identified and earmarked programs for funding projects in this area to enable a more integrated knowledge economy. The UHM EE Department is part of several NSF centers and other initiatives and successful candidates can expect high visibility for their research as well as funding support through these agencies. For details, see  https://apply.eng.hawaii.edu/apply/apply.php?pool_id=ee82957 .

Candidates with strong research records in other areas are encouraged to apply as well. We are particularly interested in research that includes interdisciplinary applications in existing areas of strength at UHM: energy, life sciences, computer privacy and security, optimization and control, signal processing and information theory.

To apply:  Applicants should follow the instructions at the following website to electronically submit their materials:  https://apply.eng.hawaii.edu/apply/apply.php?pool_id=ee82957

Review of applications is underway, but all applications submitted before Feb 15 will be given full consideration. 

The applicant should submit a cover letter specifying the position and the research area; a statement on research interests, activities, and plans; a statement on teaching philosophy, interests, and plans; a curriculum vitae detailing research and teaching accomplishments; copies of up to 5 relevant publications; official transcripts (copies/web versions acceptable, however official transcripts will be required upon hire); and the names, addresses, e-mail, and telephone numbers of at least 4 professional references (short-listed applicants will be asked to provide letters of recommendation from these references).