Computational Biology Assistant Professor of Instruction: 23-24 Academic Year

The Biology Instructional Office is seeking a candidate for a part time or full-time instructional faculty position (non-tenured) starting in 2023-2024 academic year and renewable.

Duties include teaching organized undergraduate course in Computational Biology. Course number BIO321G introduces computational methods for the analysis of nucleic acid and protein sequences, with applications towards biological problems. Student performance assessments are based on experiential learning methods. Current laboratory exercises are coded in R and Python. For further reference, a searchable database of UT course syllabi is publically available in the . Service, committee assignments, curriculum development and other professional development opportunities are available. The College is interested in and values candidates who have experience working with diverse and underserved populations, and have demonstrated a commitment to improving the diversity, equity and inclusivity of their academic communities. Salary negotiable based on experience.

A PhD is required and previous teaching experience is strongly preferred. A full-time teaching load is 3 courses per semester.

Must be eligible to work in the US on a full-time basis for any employer without sponsorship.

Please review Interfolio dossier basics online here: http://product-help.interfolio.com/m/27438/l/692488-dossier-quick-start-guide-for-applicants

In order to apply, you will need to provide:

A letter of interest,

A current curriculum vitae,

And three (3) professional references that address your teaching qualifications. References should be solicited and submitted through the Interfolio application.

The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.