166 phd-mathematical-modelling-population-modelling Postdoctoral positions at University of Oxford
Sort by
Refine Your Search
-
with cutting-edge models and technologies—including patient-derived glioblastoma organoids, CRISPR-based screens, mass cytometry, and advanced microscopy—to dissect these complex biological processes
-
that requires accurate sub-grid models (e.g., Particle-in-Cell or Vlasov codes) coupled to a hydrodynamic simulation. In general, charged-particle transport is a non-trivial task, not only because of the large
-
for the provision of research support for the ARC project on risk assessment tools in psychiatry, and particularly in child and adolescent psychiatry. About You You will have or be close to completing a PhD/DPhil in
-
Machine Learning, Human-Computing Interactions, Social Sciences, and Public Health. Applicants should hold, or be close to completion of, PhD/DPhil with research experience in computer science, statistics
-
challenge. We seek a senior computational biologist to apply these extensive in-house datasets toward the development of novel, domain-tailored machine-learning models and analytical methods. You will explore
-
of focused ultrasound, animal models of pancreatic cancer, mouse surgery and immunological laboratory techniques. About You We are looking for an enthusiastic and motivated laboratory scientist who
-
project to develop a systematic framework for reconstructing the evolutionary histories of pathogens. The role involves using viral sequence data and models of sequence evolution to investigate both
-
screening (XChem), PDB deposition and biophysical techniques including SPR, DSF and NMR. Applicants must hold a PhD in Biochemistry/ Biophysics / Chemical Crystallography or a related field (or have submitted
-
Metabolism (OCDEM) on studies related to circadian rhythms in population health. This post is part of a large, interdisciplinary research programme, offering attractive opportunities to work across
-
Oxford Population Health (Nuffield Department of Population Health) contains world-renowned population health research groups and provides an excellent environment for multi-disciplinary research