31 parallel-processing-bioinformatics PhD positions in computer-science in United Kingdom
Sort by
Refine Your Search
-
Employer
- Newcastle University
- The University of Manchester
- University of Warwick
- Durham University
- Newcastle University;
- University of Birmingham
- University of East Anglia
- Biology Centre CAS
- Manchester Metropolitan University;
- Oxford Brookes University
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- University of Dundee;
- University of Exeter;
- University of Nottingham
- University of Oxford
- University of Plymouth
- 6 more »
- « less
-
Field
-
Polymer manufacturing is highly energy intensive, and achieving net zero requires more than fuel switching. This project focuses on process systems engineering for industrial decarbonisation
-
PhD Studentship: Efficient Long-Horizon Task Execution in Physical AI (deep learning, computer vision, robotics) Number of awards: 1 Award information: Fully funded PhD studentship covering Home
-
, engineering, mathematics, physics or related field; strong programming skills; interest in ML, computer vision, robotics, embodied AI or autonomous systems; motivation for independent research and high-quality
-
a key challenge in sustainable process engineering: translating microbial electrolysis cell (MEC) technology from lab-scale innovation to robust, industrial deployment. The research will sit at
-
the energy and physical resource consumption of AI models continues to scale, there is an increasing need for new computational paradigms that draw on the efficiency and parallelism of biological
-
adaptive genomic differentiation along elevation in high tropical mountains. You will benefit from international networking, hands-on bioinformatics training and research mobility thanks to our close
-
for bioinformatics and genome biology. The student will have access to training and career development opportunities at the Earlham Institute and on the Norwich Research Park as part of the Norwich Biosciences
-
implemented in a real breeding context. Apply advanced genetic and bioinformatic tools to build a predictive model of how environmental conditions, in the context of climate change, affect yield and yield
-
efficiency. You will be embedded within a multidisciplinary team of experts in artificial intelligence, bioinformatics, laboratory automation and synthetic biology. While the wider team develops AI-driven
-
, purified and tested for biological activity together, in a single operation taking as little as a week. You will apply this new approach to real drug targets in cancer, working at the interface of synthetic