The Ethics Fellowship

The Stanford Center for Biomedical Ethics (SCBE) and announce two to three post-doctoral fellowship positions focused on exploring the ethical considerations associated with using artificial intelligence and machine learning (AI/ML) to discover transformational medicines and to deliver improved clinical outcomes. The postdoctoral fellows will conduct independent research on ethical, legal and social considerations arising from the use of AI in the pharmaceutical industry, from early-stage drug discovery efforts to downstream clinical applications. The post-doctoral fellowship positions are available as part of the Stanford Training Program in Ethical, Legal, and Social Implications (ELSI) Research and at the Center for Integration of Research on Genetics and Ethics (CIRGE). Candidates from underrepresented groups are strongly encouraged to apply.


About is a global network of researchers centered around AI hubs in London and San Francisco — where experts from various quantitative fields consider problems from different perspectives. The team consists of a diverse mix of scientists, software engineers, clinicians, and ML researchers, who carry out their own research, develop ML algorithms and AI products, and collaborate with an interdisciplinary team of experts from top machine-learning researchers at Cambridge and Oxford to Silicon Valley software engineers. It is this approach to technology that sets GSK apart, says Dr Hal Barron, a medical doctor, formerly at biotech pioneer Genentech and now chief scientific officer and president of R&D at GSK. “It’s genetics, functional genomics and the interpretation of the data they generate with machine learning that forms the core of our strategy. What machine learning has been able to do—particularly over the past two or three years—is deconstruct these massive data sets and elucidate the relationships that the various genes have with each other.” Machine learning could help with drug discovery in countless ways. Among them are adaptive clinical trials in which machine learning assists in the identification, approval and distribution of treatments and vaccines. It could also help develop individualized treatments, nudging the pharma industry away from a “one drug for everyone” approach and towards treatment based on an understanding of which drugs will work for whom.

About the Stanford Center for Biomedical Ethics

Established in 1989, the Stanford Center for Biomedical Ethics (SCBE) is an interdisciplinary hub for faculty who do research, teaching, and service on topics in bioethics and medical humanities. SCBE and its faculty have been widely recognized for leadership on a range of issues, such new approaches to studying the ethical issues presented by new technologies in biomedicine, including Artificial Intelligence, CRISPR and Gene Therapy, Stem Cell Research, Synthetic Biology, and the Human Brain Initiative. SCBE was among the first in the field to be designated by NIH as a Center for Excellence in Ethical, Legal and Social Issues (ELSI) in Genetics and Genomics. And SCBE is now the Coordinating Center for ELSI research at the National Human Genome Research Institute. SCBE faculty teach throughout Stanford, from large undergraduate courses to ethics courses taken by all medical students. SCBE offers training for medical students who choose to specialize in biomedical ethics and medical humanities, as well a highly-rated research ethics seminar taken by over 350 graduate students and fellows a year. 

How to Apply

To apply, please fill in the application form here! Application deadline: Rolling review of applications for a start date between January and October 2022. For questions, please email the Fellowship Coordinator, Yvette Dunmore (  

Program Leadership

Russ B. Altman

Kenneth Fong Professor and Professor of Bioengineering, of Genetics, of Medicine (General Medical Discipline), of Biomedical Data Science and, by courtesy, of Computer Science Bioengineering

David Magnus

Thomas A. Raffin Professor of Medicine and Biomedical Ethics and Professor (Teaching) of Medicine (Primary Care and Population Health)

Mildred Cho

Professor (Research) of Pediatrics (Center for Biomedical Ethics) and of Medicine (Primary Care and Polulation Health)

Program Fellows

Artem Trotsyuk

Artem Trotsyuk, PhD received his Ph.D. in Biomedical Engineering from Stanford University in 2022 and a Master’s in Computer Science, AI Specialization Track, in 2021. His BS is in Biological Sciences, with an emphasis in Neurology, Physiology, and Behavior, from UC Davis. In 2020, he was a McCoy Family Center for Ethics in Society Fellow, and in 2019 an Enhancing Diversity in Graduate Education (EDGE) Fellow. In 2019 he was named a Forbes 30 under 30 Scholar. He has experience in venture capital and consulting in biotechnology and health policy. Some of his recent work includes outlining risks associated with data misuse and developing frameworks for the ethical use of patient data. 

Carole Federico

Carole Federico, PhD, MSc received her Ph.D. in Experimental Medicine from McGill University in 2020 and a Master of Science in Bioethics in 2013. Her doctoral work identified inefficiencies in the drug development process. It led to a call for new forms of oversight to evaluate preclinical evidence supporting first-in-human trials. She was a fellow in the Stanford Training Program in Ethical, Legal, and Social Implications Research at the Stanford Center for Biomedical Ethics and a member of the Stanford Program on Research Rigor and Reproducibility (SPORR). Her recent work has investigated potential barriers to ethical AI/ML development and whether traditional clinical ethics frameworks organized around the drug development pipeline are suited for the ethical analysis of AI/ML. 

Abdoul Jalil Djiberou Mahamadou

Abdoul Jalil Djiberou Mahamadou, PhD received his Ph.D. in Computer Science in 2021, a MSc in Computer Science, and a Master of Engineering in Applied Mathematics in 2018 from Clermont Auvergne University. His Ph.D. dissertation focused on the development of new unsupervised machine learning models and their applications to health data mining. In 2019, Dr. Djiberou was named the best Nigerien student in France based on academic performance by the Réseau des Etudiants Nigériens de France. Prior to his appointment at Stanford, Dr. Djiberou was a Mitacs Industrial Postdoctoral Fellowship at Simon Fraser University where he worked on the identification of lifestyle factors contributing to successful cognitive aging in older adults’ population. Part of his current work focuses on developing new techniques to account for unobserved variables such as cultural factors in algorithmic fairness under changing environments.