Sort by
Refine Your Search
-
. To address these questions, we combine a series of interdisciplinary approaches ranging from experimental embryology and fluorescent microscopy to mathematical modelling. The lab is highly interdisciplinary
-
an available option. Applicants with a range of academic subject backgrounds are welcomed, including natural sciences, epidemiology, engineering, statistics and applied mathematics with experience and
-
available option. Applicants with a range of academic subject backgrounds are welcomed, including natural sciences, engineering, statistics and applied mathematics with experience and/or growing interest in
-
We are seeking to appoint a Senior Bioinformatician to lead and develop cutting-edge research into genome regulation and identification of novel therapeutic targets for rare disease. You will join the Computational Rare Disease Genomics (CRDG) Team, which is led by Associate Professor Nicky...
-
We are currently inviting applications for two Postdoctoral Research Associates (PDRAs) to work with Professor Robin Thompson at the Mathematical Institute, University of Oxford. These are two fixed
-
inference attacks, to mitigate privacy leaks in MMFM. You will hold a PhD/DPhil (or be near completion) in a relevant discipline such as computer science, data science, statistics or mathematics; expertise in
-
flow control, in collaboration with researchers at the Arizona State University. The position would suit a theoretician with a strong control engineering or mathematical background. The successful
-
Leedham (colorectal cancer biology), Dan Woodcock (cancer genomics), Helen Byrne (mathematical modelling), and Jens Rittscher (computational pathology and imaging AI), offering a unique opportunity to work
-
-certification, and redeployment, as well as social acceptability and policy design. About you You should hold a relevant PhD/DPhil, or be near completion, in electrical engineering, economics, applied mathematics
-
Engineering, Mathematics, Statistics, Computer Science or conjugate subject; strong record of publication in the relevant literature; good knowledge of machine learning algorithms and/or statistical methods