The Data Science Institute (DSI) at Brown University is seeking to hire an Assistant Professor of the Practice of Data Science. (Professors of the Practice are faculty who are hired to enhance Brown’s pedagogical mission and whose qualifications are earned primarily through professional experience rather than scholarly credentials.) The initial appointment would be for a 3-year period, renewable with potential for promotion and longer-term appointments. The positions include teaching in our in-person Data Science Master’s program and the online Master of Science in Data Science: Policy, Governance & Society, advising, and additional responsibilities.

The Assistant Professor of the Practice should have a solid background in mathematics (linear algebra, calculus), Deep Learning, Generative AI, Large Language Models, and potentially Machine Learning Operations. The incumbent will teach a Deep Learning course (currently offered by the CS Department as CSCI1470/2470), a new mandatory course on Gen AI and LLMs, and an elective course on ML Ops. All three courses are offered within the in-person master’s program. This candidate will also offer an online summer course for the incoming master’s students to teach/review the required linear algebra, calculus, stats/probability, and python coding required to succeed in these challenging courses.

Qualified candidates will have experience mentoring entry-level data scientists or master’s/undergraduate students to develop career pathways. We seek candidates who will contribute to our overall intellectual culture; this in-person position will be included in faculty meetings, can advise undergraduate research projects, and can participate in graduate research with the rest of the faculty.  

• Qualifications

In selecting candidates, we will consider an experienced track record of being the primary instructor in data science related courses and/or relevant work experience in industry and managing a data science team; evidence of effective teaching; evidence of effective mentoring; and compatibility with the area needs and interests of the DSI, as well as potential for effective participation in DSI or university activities. For all applicants, we will consider potential for impact beyond Brown (through teaching, significant system building, outreach, or other professional activities, as appropriate for the candidate). A strong record of industry experience, advanced degree preferred.

• Application Instructions

Applicants should submit a CV or resume, a teaching statement (outlining their approach to teaching and learning; this can include discussion of relevant experience outside the classroom), a statement addressing how they would contribute to the research and/or teaching missions of our diverse and inclusive university community, and the contact info of three professional references who could write a recommendation letter if the candidate is short-listed. Applications accepted through Interfolio: https://apply.interfolio.com/173924. Applications will be reviewed starting November 15, 2025; we will accept applications until the position is filled.

The Data Science Institute at Brown University is seeking a Course Developer and Instructor (adjunct faculty) for a new online Master's in Data Science: Governance, Policy and Society. This is a remote position for an expert who can develop and teach a course on Machine Learning, Deep Learning, and Large Language Models, with a critical focus on the technical aspects of fairness and bias.

About the Role

This position offers a unique opportunity to join a new, innovative graduate program designed to train the next generation of data scientists. The successful candidate will work closely with Brown University's Digital Learning and Design (DLD) team to create a comprehensive, 15-week asynchronous course delivered via the Canvas learning platform. The development phase begins October 1, 2025, and the course will be taught in Summer 2026.

 Key responsibilities include:

• Developing rigorous, student-centered course content that aligns with online teaching and learning best practices.
• Integrating real-world problem sets and applications into the course material.
• Facilitating weekly synchronous sessions to enhance student engagement.
• Managing the course on the Canvas Learning Management System, including grading and student communication.
• Providing consistent academic support and mentorship to students.

The Course

The course offers a comprehensive introduction to machine learning, deep learning, and generative AI. It is distinguished by its unique focus on the technical aspects of detecting and remediating fairness and bias in these models. The curriculum will cover classical machine learning techniques and their susceptibility to bias, as well as the emerging fields of deep learning and large language models (LLMs). Students will explore key concepts such as backpropagation, pretraining, fine-tuning, and alignment strategies like Deep Policy Optimization (DPO) and Reinforcement Learning from Human Feedback (RLHF), all with a focus on ethical application.

Qualifications

• A master's degree or higher in Data Science, Statistics, Computer Science, or a closely related field is required.
• A minimum of two years of experience as a Teaching Associate, Adjunct Faculty, or Instructor in a university setting, or advanced expertise in the field gained through professional experience.
• Demonstrated proficiency in the course content, particularly in the technical aspects of ML/DL/LLM fairness and bias.
• Experience in developing and teaching online courses using a Learning Management System like Canvas is preferred.
• A collaborative and self-disciplined individual who can promote an inclusive environment and contribute to a diverse community of perspectives.

Compensation

This position offers a stipend of $14,000, which will be paid in two installments: half at the start of the development phase and half upon completion. The same stipend is awarded each time the faculty member teaches the course. The role requires an average commitment of 5 to 10 hours per week during development.

How to Apply

To be considered for this position, please submit the following materials via this form. 

• A current Curriculum Vitae.
• A cover letter addressing your specific qualifications to teach this unique course, focusing on your expertise in detecting and remediating fairness and bias issues, and the reasons for your interest in the position.
• The names and contact information for three professional references.

Questions can be addressed to amanda_whittaker@brown.edu.