Assistant Teaching Professor in Biology presso Brown University

Brown University’s Division of Biology and Medicine is a vibrant hub of discovery, education, and innovation, bringing together scientists, educators, clinicians, and trainees to tackle some of the most pressing challenges in biomedicine and health. With a commitment to offering academic programs of the highest quality in our areas of strength, the Division has recently launched the Master of Science in Health Informatics Program (MHIP), a program at the intersection of data, technology, artificial intelligence (AI), and health.

To support the MHIP, the Division seeks an Assistant Teaching Professor in Biology, who will be appointed in Biology Education, a section of the Division’s Medical Science Academic Unit. Biology Education is home to Teaching Professors, Lecturers, Adjuncts, and Professors of the Practice who are dedicated to teaching, advising, and advancing academic programming for students across the Program in Biology’s undergraduate concentrations as well as its master’s and doctoral offerings. Within this dynamic environment, the successful candidate will provide expertise in teaching and curriculum development for MHIP students, while also contributing courses that serve the broader biomedical graduate community, which includes two other master’s programs and seven doctoral programs.

The ideal candidate will have a strong background in statistics and AI with demonstrable application in biology or health, a commitment to fostering an inclusive learning environment, and experience in successfully developing and leading graduate-level courses for biomedical trainees. Experience in the development and use of statistical and AI methodologies to analyze and interpret large sets of biological or health data will be viewed favorably. Experience with AI implementation, including assessing the ethical, legal, and social implications of AI in health care, is also desirable. The successful candidate will be passionate about teaching and committed to enhancing the analytic and implementation skills of our graduate students with career goals in academia, health care, government, and industry.

Teaching contributions will include instruction of up to four graduate-level courses per year. Two of these courses will be Foundations in Statistics for Biology and Medicine and Artificial Intelligence in Healthcare. In addition to MHIP students, these courses will be open to graduate students in aligned graduate programs across the Division. Additional courses will be developed collaboratively with the appointee, MHIP Co-Directors, and divisional leadership to ensure that teaching assignments reflect both curricular needs and the appointee’s expertise and interests. Alongside teaching, the appointee will play an active role on the MHIP leadership team, helping to shape the curriculum, advising students, strengthening cyberinfrastructure for student support, and advancing other key program initiatives that provide a next-generation training experience for future leaders in health informatics and AI.

Major responsibilities include:

● Course Development and Instruction
   ○ Teach graduate-level courses designed for multidisciplinary master’s and doctoral students in the biomedical sciences, with emphasis on introductory and intermediate knowledge and skills at the intersection of data, technology, AI, and health.
   ○ Assume primary responsibility for Foundations in Statistics for Biology and Medicine (BIOL 2025), a course with expected enrollment of ~100 students, that provides essential statistical knowledge and skills for graduate-level research. Using statistical analysis software, students in this course engage in hands-on analysis of biological and medical data, covering topics such as data cleaning and shaping, descriptive statistics, probability distributions, parametric and non-parametric tests, correlation, mean differences, analysis of variance, regression (linear and logistic), and graphical presentation of data, as well as an introduction to more advanced methods.
   ○ Develop and teach Artificial Intelligence in Healthcare (BIOL 2595), a course with expected enrollment of ~40 students, which introduces students to the principles and applications of AI in health contexts. Students will explore AI’s impact on clinical decision-making, translational bioinformatics, and precision medicine, focusing on contemporary methods and their historical context. They will also critically assess the strengths and limitations of AI technologies in clinical practice.
   ○ Develop and offer additional courses in collaboration with the MHIP Co-Directors and divisional leadership to align with curricular needs and the appointee’s expertise and interests.
   ○ Integrate training and teaching experiences to customize courses that serve students across graduate programs.
   ○ Employ evidence-based pedagogy, emphasize programming skills (e.g., Julia, Python, or R), guide hands-on data analysis and implementation projects, and foster an inclusive and supportive classroom environment across all teaching.

● Health Data and Computing Resources
   ○ Provide guidance for enhancing and maintaining health data, computing environments, and software tools for education and training in health informatics, data science, and AI.
   ○ Coordinate with other university units (e.g., Office of Information Technology, University Library, and Division of Research) for institutional health data governance and cyberinfrastructure to meet student needs.
   ○ Guide students in using health data and computing resources in courses and for thesis projects.

● Student Admissions and Academic Support
    ○ Serve as a member of the MHIP Admissions Committee, which includes reviewing applications, conducting interviews, and making recommendations for admissions.
   ○ Contribute to continuous quality improvement for MHIP. Provide timely academic guidance and support to students, including holding student hours and offering feedback on assessments.
   ○ Commit to fostering a healthy learning environment with inclusive teaching and learning practices for larger classroom settings.

Teaching track faculty at Brown are part of the regular faculty with voting rights. The 10-month position is expected to start in September 2026 and will be based in Biology Education in the Division of Biology and Medicine, with the opportunity for a secondary appointment in one of the Program in Biology academic departments. The initial appointment would be a renewable 3-year appointment, depending on performance and review. Opportunities to supplement income in July and August may be available through additional teaching engagements and participation in extramurally funded programs led by MHIP faculty. Paid Scholarly Leaves are available after accumulating the requisite number of semesters in the position.

The Division of Biology and Medicine strives to build an inclusive learning environment for all, and so we are particularly interested in candidates whose teaching, advising, service, and scholarship (if applicable) can further our efforts. Brown has a longstanding commitment to diversity and inclusion as central to fulfilling its academic mission to advance knowledge and understanding. Brown strives to draw together a community that reflects the world beyond our campus, knowing that a diversity of perspectives, ideas, and experiences helps to overcome stereotypes and drives academic excellence, innovation, discovery, and a better understanding of the human condition.

As an EEO employer, Brown University provides equal opportunity and prohibits discrimination, harassment and retaliation based upon a person’s race, color, religion, sex, age, national or ethnic origin, disability, veteran status, sexual orientation, gender identity, gender expression, or any other characteristic protected under applicable law, in the administration of its policies, programs, and activities. The University recognizes and rewards individuals on the basis of qualifications and performance. The University maintains certain affirmative action programs in compliance with applicable law.

For this position, Brown does not sponsor the H-1B visa classification to scholars who need immigration sponsorship in order to enter the U.S. and commence lawful employment under the terms of their appointment.

Requirements

● Education: Doctoral degree in Biostatistics, Statistics, Data Science, Computer Science, Biomedical Informatics, or a closely related field.

● Experience: Course development and teaching experience in higher education is required, and experience teaching computational approaches to groups of students with varying prior training will be viewed as a major strength. Candidates with prior experience in the development and use of statistical and AI methodologies to analyze biological or health data in real-world settings is strongly preferred. Experience with student advising and mentoring is preferred.

● Communication and Collaboration: Excellent verbal and written communication skills. Ability to work collaboratively with different stakeholders: students, faculty, senior administrators, and staff. Ability to engage and motivate students with various backgrounds and skill levels. Exemplary professionalism as demonstrated by excellent communication skills, collegiality, and ability to meet the needs of a large number of stakeholders.

● Commitment: Strong commitment to inclusive teaching practices and high-quality teaching. Ability to work collaboratively with faculty and staff across disciplinary boundaries. Prior experience in designing academic programs in health AI is preferred.

Interested candidates should submit:

1. Cover Letter that summarizes interest and qualifications.
2. Curriculum Vitae.
3. Teaching Statement: A two-page statement describing contributions to higher education: instruction, course design and assessment, curricular contributions, and advising. The teaching statement should include future goals as an educator and provide examples of why and how inclusive classroom practices, alongside impactful teaching strategies, have been effective in current/past courses.
4. Summary of Teaching Evaluations (where applicable).

Candidates should address how they would contribute to the research and/or teaching missions of our diverse and inclusive university community. Candidates should also suggest up to three references who will be contacted for letters after the initial screening of applicants. The names, affiliations, titles, and contact information of these references should be included in the cover letter.

Full consideration will be given to all applications received by December 15, 2025. Applications received after the priority deadline may be reviewed until the position is filled or the search is closed.