Professor

Alexander Medvinsky

Has open position

Professor at The University of Edinburgh

The University of Edinburgh

United Kingdom

Research Interests

Stem Cell Biology

10%

Medical Science

10%

Biology

10%

Machine Learning

10%

Precision Medicine

10%

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Positions(1)

Publisher
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Alexander Medvinsky

The University of Edinburgh

.

United Kingdom

PhD Studentship in Precision Medicine: Biomarker Analysis for Umbilical Cord Blood Transplantation Outcomes

This PhD studentship at The University of Edinburgh offers an exciting opportunity to contribute to the advancement of precision medicine through the analysis of biomarkers associated with umbilical cord blood (UCB) transplantation outcomes. The project is embedded within a consortium funded by an MRC DPFS grant, aiming to develop robust molecular biomarker-based test systems for optimal UCB selection in clinical transplantations. The research is closely linked to the Medvinsky laboratory, renowned for expertise in mouse and human haematopoietic stem cell biology and xenotransplantation models. Umbilical cord blood is a critical resource for haematopoietic cell transplantation, especially when matched adult donors are unavailable. However, variability in UCB samples can lead to delayed haematopoietic reconstitution and biased lineage differentiation. This project seeks to address these challenges by identifying molecular and morphological traits that correlate with successful transplantation outcomes. Preliminary xenograft analyses have already revealed promising molecular markers, and the PhD will expand this work to discover additional morphological traits using advanced AI image-based analysis of UCB cells transplanted into immunocompromised NSG mice. The student will benefit from a highly interactive research environment, co-supervised by experts in stem cell biology, machine learning, and clinical haematology. Training will include multi-lineage analysis of blood samples using flow cytometry and blood smears, in vitro differentiation assays for myeloid and lymphoid lineages, and hands-on experience with machine learning techniques applied to biomedical imaging data. Applicants should be motivated to work at the intersection of biology, medicine, and computational science. While specific entry requirements are not detailed, a strong background in biological sciences, biomedical research, or computational analysis will be advantageous. The application process requires submission via the EUCLID system, including a completed Precision Medicine Recruitment Form and supporting documents such as a CV. Prospective candidates are encouraged to attend the Q&A session with project supervisors for further insights. This studentship does not specify funding details, so applicants should clarify funding status during the application process. The deadline for applications is 12 January 2026, and early preparation of documents is recommended.

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