Adjunct Instructor in 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. Application Process: Interested candidates should submit: A cover letter highlighting relevant qualifications and teaching experience. A current CV or resume. Contact information for three professional references. (Optional) Examples of teaching materials or professional publications related to leadership and industry innovation. 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