-
Faculty of Computing, Mathematics, Engineering & Natural Sciences Funded PhD Project (UK or International Students) Funding provider: Northeastern University London (NU London) Subject areas
-
high-impact publications will be generated during the project, to be presented both in computer science-related venues (e.g. CVPR, NeurIPS, MICCAI) as well as at medical conferences (e.g. ISMRM, ESMRMB
-
are expected to gain) a first-class honours degree or equivalent in a suitable field such as engineering, computer science, physics, or atmospheric science. Funding This studentship is for 3.5 years and will
-
when the project commences. Applications are invited from candidates with (or who are expected to gain) a first-class honours degree or equivalent in a suitable field such as engineering, computer science
-
Civil Engineering or Computational Physics. They should demonstrate aptitude for original research. The candidate should possess a good understanding of construction processes and data processing
-
methods could alleviate this limitation by leveraging large amounts of un-annotated datasets. These techniques remain however largely unexplored in the field of medical video analysis. The School of Science
-
to power engineering, mathematics, computing and energy economics. The successful candidate will have excellent understanding in the fields of power system operations and economics. Experience in data
-
, or higher) degree in Mathematics, Computer Science, Statistics, Engineering, Physics, or related STEM areas. Scholarship: The studentship is for 3 years and will provide an annual tax-free stipend of £20,662
-
machine learning to CFD-generated datasets. The ideal applicant is a fresh graduate in engineering or in a closely related discipline, with a track record of achievements at the top of their cohorts
-
prediction. This project is a collaborative effort between the School of Computing & Mathematical Sciences (CMS) and the School of Engineering (SoE) to utilise expertise and facilities between two schools