Tenure-Track Assistant Professor – Interfaces of Data Science and Computational Science

The International Society for Bayesian Analysis; Austin (TX); On-site; USD 70,000 - 120,000; Full time

Job summary

The Oden Institute at the University of Texas is seeking a Tenure-Track Assistant Professor in Data and Computational Science. This role involves establishing a research program at the intersection of advanced mathematical, statistical, and computational techniques. Candidates should have a strong potential for teaching and research excellence, engaging with challenging applications in various scientific fields.

Qualifications

• Strong connection to applications in science, engineering, or medicine.
• Demonstrated potential for teaching excellence and active research.
• Commitment to interdisciplinary research program.

Responsibilities

• Pursue an active research program.
• Teach graduate and undergraduate courses.
• Supervise students in research.

Skills

Teaching

Research

Interdisciplinary collaboration

Education

Ph.D. or equivalent degree

Job description

Tenure-Track Assistant Professor – Interfaces of Data Science and Computational Science

Description: The Oden Institute for Computational Engineering and Sciences at the University of Texas invites applicants for a tenure-track faculty position at the interfaces of Data Science and Computational Science. Areas of interest include, but are not limited to, computational statistics, machine learning, graph theory, randomized linear algebra, and tensor methods. Candidates should have a strong connection to challenging applications in science, engineering, and/or medicine. Candidates should be committed to establishing an interdisciplinary research program at the intersection of advanced mathematical, statistical, and computational techniques, high-performance computing, and target applications.

The Oden Institute is an interdisciplinary research and education institute working to transform science, engineering, and medicine through computation. Oden Institute research is building the mathematical and statistical foundations for predictive science, data science, and machine learning; developing next-generation computational science on advanced computing platforms; and addressing grand challenges in science, engineering, and medicine through computational modeling, scalable algorithms, and high-performance computing. Full details of the Oden Institute are available at https://www.oden.utexas.edu/.

Qualifications: Tenure track positions require a Ph.D. or equivalent degree in a relevant area and a demonstrated potential for excellence in teaching and research. Successful candidates are expected to pursue an active research program, to teach both graduate and undergraduate courses, and to supervise students in research.

Application Instructions: Interested applicants should submit the following: cover letter; description of research accomplishments including current and future research plans (limited to 4 pages); statement of teaching experience including goals and philosophy; curriculum vitae including a list of publications. Candidates are also required to request three letters of recommendation using the Interfolio website, which will email the referees directly with instructions on uploading letters of recommendation. Only the required materials will be reviewed. Evaluation of applications will begin on November 30, 2019, and will continue until the position is filled. Therefore, applications completed by November 30, 2019 will be assured full consideration. For questions, please email [e-mail].

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. Background check will be conducted on applicant selected.