145 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at University of Oxford
Sort by
Refine Your Search
-
and clinical neuroscience. This project involves development of machine learning methods for mapping the relationships between diffusion MRI (dMRI) and phase-sensitive OCT (PS-OCT) in the same tissue
-
tutoring of undergraduates and graduate students. Applicants should hold a PhD, or be close to obtaining of one, in physics or a related field and have a background in computational plasma physics
-
Health, Geography, Global Affairs, or a related field, possess sufficient specialist knowledge in the discipline to work within established research programmes, experience writing computer code in Stata
-
in Python, or demonstrated ability to rapidly acquire fluent knowledge of new programming languages, libraries, and platforms. A background and/or interest in mathematics or computer science would be
-
data from a variety of sources, including Spatial Transcriptomics and multiplex Spatial Proteomics platforms and developing skills in computational biology and mathematical spatial analysis via
-
. The advances made will contribute to our active existing research programme in which utilises THz technologies for optical-pump-terahertz-probe experiments to extract mobility values of semiconductors. The role
-
or statistical machine learning. They will have excellent communication skills, including the ability to write for publication, present research proposals and results, and represent the research group at meetings
-
algorithms and machine-learning models on real-world robot platforms are required. Proficiency in programming languages such as Python and C++/Rust is also necessary. For informal inquiries, please get in
-
The University also runs an enormous amount of social groups and sports clubs for those looking for more than just a great place to work. About you Applicants should hold a PhD/DPhil or be near completion of a PhD
-
requires experience in single-molecule imaging biophysics and expertise in at least two of the following: nanopore technology, optical microscopy, machine learning, mass spectrometry, complex optical set-up