Adjunct Instructor in Artificial Intelligence & Machine Learning in Drug Development

brandeis; Waltham (MA); On-site; USD 73,000 - 89,000; Full time

Job summary

Brandeis University seeks qualified candidates for a course on Artificial Intelligence & Machine Learning in Drug Development. The role involves designing a syllabus, creating course content, and leading online discussions using real biotech case studies.

Ideal applicants will hold a PhD or MS in a relevant field, with deep knowledge of AI/ML applications in pharma and strong communication and analytical skills. Teaching experience and familiarity with online tools are preferred.

Qualifications

• Current active employment in the relevant biotech or pharmaceutical industry.
• Deep knowledge of course-specific applications and industry practices.
• Ph.D. or M.S.
• Strong communication and analytical skills.
• Preferred: Previous teaching experience or experience delivering professional training.
• Preferred: Familiarity with online instructional tools and platforms.

Responsibilities

• Design a syllabus following program chair guidance and the syllabus template
• Create content aligned with course outcomes, integrating personal expertise
• Facilitate online discussions and provide timely, relevant feedback
• Maintain the course site and update content in the Moodle LMS
• Lead students in AI model development and interpretation using biotech case studies.
• Help students critically assess the limitations and ethics of AI in pharmaceutical innovation.

Skills

Communication skills

Analytical skills

Education

Ph.D. or M.S. in relevant field

Tools

Python

scikit-learn

TensorFlow

Job description

Course Title: Artificial Intelligence & Machine Learning in Drug Development

This course explores the use of AI and ML in pharmaceutical R&D. Topics include data preprocessing, predictive modeling, and applications in target identification, drug screening, and clinical trial optimization. Students gain hands-on experience using tools and algorithms to analyze real-world biotech data sets.

Qualifications

Qualified candidates will have Subject Matter Qualifications in the following areas.

Required:

• Current active employment in the relevant biotech or pharmaceutical industry
• Deep knowledge of course-specific applications and industry practices
• Ph.D. or M.S.
• Strong communication and analytical skills

Preferred:

• Previous teaching experience or experience delivering professional training
• Familiarity with online instructional tools and platforms

General Responsibilities

• Design a syllabus following program chair guidance and the syllabus template
• Create content aligned with course outcomes, integrating personal expertise
• Facilitate online discussions and provide timely, relevant feedback
• Maintain the course site and update content in the Moodle LMS
• Lead students in AI model development and interpretation using biotech case studies.
• Help students critically assess the limitations and ethics of AI in pharmaceutical innovation.

General Skill Requirements

• Strong interpersonal skills and the ability to foster student engagement
• Written communication skills, especially for online learning
• Ability to manage time effectively and respond promptly to students
• Proficiency in applying machine learning tools (e.g., Python, scikit-learn, TensorFlow) to drug discovery datasets.

About the Master of Science in Applied Biotechnology & Enterprise

This program prepares students to innovate and lead in the fast-paced biotech industry, integrating scientific knowledge with business strategy. Students learn through project-based, real-world applications.

All GPS courses are 8-weeks long and taught asynchronously online.

About GPS Faculty

GPS Faculty are active industry professionals who teach part-time, online. Our instructors hold at least a master's degree, and many have terminal degrees and professional certifications. Previous teaching experience is not required; GPS provides full training.

This appointment is to a position that is in a collective bargaining unit represented by SEIU Local 509.

The compensation for this position is $6573.15

Pay Range Disclosure

The University's pay ranges represent a good faith estimate of what Brandeis reasonably expects to pay for a position at the time of posting. The pay offered to a selected candidate during hiring will be based on factors such as (but not limited to) the scope and responsibilities of the position, the candidate's work experience and education/training, internal peer equity, and applicable legal requirements.

Equal Opportunity Statement

Brandeis University is an equal opportunity employer which does not discriminate against any applicant or employee on the basis of race, color, ancestry, religious creed, gender identity and expression, national or ethnic origin, sex, sexual orientation, pregnancy, age, genetic information, disability, caste, military or veteran status or any other category protected by law (also known as membership in a "protected class").