Part-time Faculty - Health Data Science & AI

Saint Louis University-posted 1 day ago
Part-time
SLU Saint Louis, MO
1,001-5,000 employees
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Founded in 1818, Saint Louis University is one of the nation’s oldest and most prestigious Catholic universities. SLU, which also has a campus in Madrid, Spain, is recognized for world-class academics, life-changing research, compassionate health care, and a strong commitment to faith and service. Adjunct Assistant/Associate Professor – Health Data Science and Artificial Intelligence Applications in Medicine Department of Health and Clinical Outcomes Research Saint Louis University School of Medicine Position Summary The Department of Health and Clinical Outcomes Research at Saint Louis University School of Medicine invites applications for Adjunct Assistant or Associate Professor positions to teach graduate-level courses and mentor students in applied health data science and artificial intelligence in medicine.

  • Adjunct faculty will teach one or more of the following courses or related electives within the Department’s data science and AI curriculum: Privacy, Ethics, Regulation & Policy Introduction to Artificial Intelligence Predictive Modeling and Machine Learning Image Processing and Deep Learning Bioinformatics & Biomedical / Clinical Data Analysis Natural Language Processing and Large Language Models Reinforcement Learning for Clinical Decision Making Telehealth & Telemedicine AI for Precision Medicine & Genomics & Diagnostics Research in Medicine
  • Develop and deliver engaging, practice-based course materials.
  • Mentoring students on applied research and analytics projects using real-world datasets.
  • Collaborating with program leadership to ensure content quality, alignment with learning objectives, and current best practices in AI and health data analytics.
  • Participating in departmental meetings or student events, as appropriate for adjunct appointments.
  • Ph.D. or equivalent terminal degree in Health Data Science, Biomedical Informatics, Computer Science, Biostatistics, or a related field.
  • Demonstrated expertise in one or more areas of artificial intelligence, data science, or computational health analytics.
  • Proficiency with relevant tools and languages (e.g., Python, R, SQL, TensorFlow, PyTorch, SAS).
  • Strong communication skills and a commitment to high-quality, student-centered graduate teaching.
  • Experience teaching graduate courses in AI, data science, or health informatics.
  • Applied or research experience involving AI deployment in healthcare, biomedical, or clinical contexts.
  • Familiarity with regulatory, ethical, and equity considerations in digital health and AI.
  • Record of scholarly or professional contributions in data-driven healthcare innovation.
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