Adjunct Faculty - Pharmaceutical Economics and Policy (PEP) On-Line Artificial Intelligence: Machine Learning and Deep Learning

Description

The School of Pharmacy - Boston seeks an adjunct faculty member to deliver high quality learning experiences and education for students in the Pharmaceutical Economics & Policy Program (PEP). More specifically, we are looking for candidates to teach online, asynchronously, a course on Artificial Intelligence (AI): Machine Learning (ML) and Deep Learning (DL), focusing on supervised learning, ensemble methods and boosting, neural networks, support vector machines, kernel methods, clustering and unsupervised learning, maximum likelihood, graphical models, hidden Markov models, inference methods, and computational learning theory for graduate students in the master's in PEP program. This course is an intermediate level course, designed to help students gain hands-on experience in building, training, and optimizing models using homework programming assignments reflecting real-world health data. More details about course content can be delivered during the interview process. The following criteria are sought in applicants:

• Deliver didactic instruction in the Pharmaceutical Economics and Policy Program on the Boston campus.
• Provide students with an approved syllabus that includes course objectives and learning outcomes, teaching methodology, attendance policies in line with those of the School, texts and readings, assignments and deliverables, timelines and evaluation criteria.
• Provide engaging assignments that demonstrate the real-world applications of concepts covered.
• Uses the University's learning management system to post syllabus, assignments and other materials and to communicate with students
• Advises and assists students through office hours or scheduled appointments, by videoconference, phone or email, and through other University-approved mechanisms
• Additional responsibilities may be assigned by the supervisor

Requirements

Required:

• A PhD or Master's degree in Computer Science, Data Science, Biostatistics, Epidemiology, Health Informatics, or a related field.
• Strong background in machine learning, deep learning, and AI.
• Experience with healthcare applications of AI is preferred.
• Proficiency in R and/or Python and ML/DL libraries.
• Prior experience teaching at the graduate level is preferred.
• Ability to engage students in an online environment effectively.

Please attach a cover letter and a curriculum vitae/resume. Finalist candidate(s) for this position will be subject to reference checks and a pre-employment background check as a condition of employment. Applicants must be authorized to work for any employer in the U.S. MCPHS is unable to sponsor, or take over sponsorship of an employment Visa. MCPHS is also not an E-Verify institution.

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