Sort by
Refine Your Search
-
. This project will comprehensively examine the roles of this novel PrLP by: 1) Defining its roles in lysosome activity, localisation and dynamics 2) Establishing the contribution of its domains to these roles 3
-
have found that microbial interactions shape the temporal dynamics of antimicrobial resistance (AMR) in the Arctic. Moreover, there is emerging evidence from terrestrial ecosystems that antibiotics and
-
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
-
community, supported by cutting-edge research facilities and excellent training opportunities. The Norwich Research Park Biosciences Doctoral Training Programme (NRPDTP) is offering fully funded studentships
-
programming skills in Python/MATLAB, and an interest in digital twin technologies, cybersecurity and machine learning. Entry Requirements Acceptable first degree: Computer Science or related disciplines
-
Project Supervisor - Professor Rudy Lapeer The Birth4Cast “Digital Twin” aims to create a subject-specific computational biomechanics simulator of childbirth from prenatal fetal MRI scans
-
across different imaging devices, including future sensors with unknown spectral sensitivities. Training The student will be based at the Colour & Imaging Lab at the School of Computing Sciences which has
-
Butt (j.butt@uea.ac.uk ) for further information. The Norwich Research Park Biosciences Doctoral Training Programme (NRPDTP) is offering fully funded studentships for October 2026 entry. The programme
-
in RNA biology, biochemistry, and Oxford Nanopore sequencing. The Norwich Research Park Biosciences Doctoral Training Programme (NRPDTP) is offering fully funded studentships for October 2025 entry
-
Biosciences Doctoral Training Programme (NRPDTP) is offering fully funded studentships for October 2026 entry. The programme offers postgraduates the opportunity to undertake a 4-year PhD research project