53 phd-rehabilitation-engineering-computer-science PhD positions at University of East Anglia
Sort by
Refine Your Search
-
model, human organoid technology, cell and molecular biology, confocal microscopy and metagenomic sequence analysis. By deciphering the interactions between AIEC, the microbiome and the intestinal
-
will receive hands-on training in spatial data analysis, while developing conceptual understanding and critical thinking in movement ecology, marine science and conservation. You will build strong
-
We are looking for a motivated student to work on an interdisciplinary project that spans bioinformatics, microbiology and chemistry. In this 4-year PhD project, the candidate will explore and
-
for research, policy and society. The PhD will be based in the Science, Society and Sustainability (3S) research group in the School of Environmental Science and will work closely alongside researchers from
-
. The programme offers postgraduates the opportunity to undertake a 4-year PhD research project whilst enhancing professional development and research skills through a comprehensive training programme. You will
-
PhD research project whilst enhancing professional development and research skills through a comprehensive training programme. You will join a vibrant community of world-leading researchers. All NRPDTP
-
papers. Attendance at summer schools, such as the National Centre for Atmospheric Science summer school , will provide additional networking opportunities. This PhD project is in a competition for a
-
computational scientific support and funding to attend conferences, preparing the student for any career of their choice. For information on eligibility and how to apply: http://www.uea.ac.uk/phd/mmbdtp Entry
-
(Beraza and Rushworth) whose work have a strong translational aim. This team will train the PhD student in a series of preclinical in vivo models; molecular biology and immunology methodologies; and complex
-
of short-axis MR image sequences. Training You will be based at the Vision Computing Lab within the School of Computing Sciences, which specializes in deep learning for medical image analysis and neural