Full-Time, Teaching-Track Faculty Position in Quantitative and Computational Biology

USC Dornsife College of Letters, Arts, and Science; Los Angeles (CA); On-site; USD 80,000 - 90,000; Full time

Job summary

The Department of Quantitative and Computational Biology at USC Dornsife invites applications for a full-time teaching-track faculty position (instructor or lecturer) in Quantitative and Computational Biology. The successful candidate will teach statistics and computational biology courses and contribute to course development while maintaining a strong research/education profile in quantitative biology.

Applicant should have a Ph.D.

Qualifications

• PhD or equivalent degree by time of appointment.
• Experience as instructor of record in computational biology or related field.
• Strong track record as researcher and educator in quantitative biology; rigorous training in statistics/biostatistics.

Responsibilities

• Teach QBIO 305 Statistics for Biological Sciences and related courses.
• Develop and teach additional computational biology courses and materials.

Skills

Statistics

Quantitative biology

Biostatistics

Education

PhD or equivalent

Job description

The Department of Quantitative and Computational Biology (QCB) in the Dana and David Dornsife College of Letters, Arts and Sciences of the University of Southern California invites applications for a teaching-track faculty position, instructor or lecturer, of Quantitative and Computational Biology. The ideal candidate will have expertise in quantitative, computational, and statistical approaches to solve fundamental questions in biology and biomedicine. The teaching activities of the successful candidate will primarily entail the teaching of statistics courses, including multiple sections of QBIO 305 Statistics for Biological Sciences, as well as the teaching and development of other computational biology courses. It is expected for the successful candidate to have a track record as researcher and educator in quantitative approaches to biology and to have rigorous training in statistics or biostatistics.

The successful candidate will join the QCB Department, a group of 12 tenured/tenure-track, teaching, and research core faculty members. The QCB Department has a 45-year history of computational biology research and education, including a rigorous Ph.D. program in Computational Biology and Bioinformatics with 60 students, a Master’s program in Quantitative and Computational Biology with 25 students, and an undergraduate major in Quantitative Biology with 130 students that represents modern biology education at the interface of biology, mathematics, and computer science. Members of the QCB Department work closely with other faculty in the Dornsife College of Letters, Arts and Sciences, the Viterbi School of Engineering, the Keck School of Medicine, and other USC schools. The QCB Department is located on the University Park Campus in Los Angeles, California. More information on the QCB Department can be found at: http://dornsife.usc.edu/qcb/

The anticipated start date is August 16, 2027. Applicants must have received a Ph.D. (or equivalent) degree by time of appointment and ideally have at least one semester experience as instructor of record of a computational biology course at a higher education institution. Review of applications will begin December 1, 2026. In order to be considered for this position, applicants are required to submit an electronic USC application; follow this job link or paste in a browser: https://usccareers.usc.edu/job/los-angeles/full-time-teaching-track-faculty-position-in-quantitative-and-computational-biology/1209/94300113920. Please submit a cover letter, a curriculum vitae, a teaching statement, 3 current external letters of recommendation, and any other evidence of teaching effectiveness, including available teaching evaluations. Please direct inquiries to Rokas Oginskis ([e-mail])

The annual base salary range for this position is $80,000 - $90,250. When extending an offer of employment, the University of Southern California considers factors such as (but not limited to) the scope and responsibilities of the position, the candidate’s work experience, education/training, key skills, federal, state and local laws, contractual stipulations, grant funding, as well as external market and organizational considerations.