263 computer-science-programming-languages-"UCL"-"UCL" positions at University of Nottingham
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
to different career paths and career progression. An excellent holiday allowance of 27 days (pro rata), plus additional university closure days and bank holidays Employee Assistance Programme and
-
Training Programme, those based within the Faculty of Engineering have access to bespoke courses developed for Engineering PGRs. including sessions on paper writing, networking and career development after
-
/computational biology/molecular biology/genomics or related area. The successful candidate will have considerable experience in computational bioinformatic analysis (R, Python or equivalent) of omics data and
-
2025 start, hosted at the University of Nottingham within the Department of Chemical and Environmental Engineering and School of Pharmacy. The project will focus on the synthesis of polymers that resist
-
in adults with cerebral palsy; this project has been funded by NIHR Programme Development Grants. You will conduct a scoping review, recruit and interview participants, analyse qualitative data
-
. You will have: 1) Post-graduate level, ideally qualified with a PhD (or close to completion) in Building Services Engineering, Mechanical Engineering, Control Engineering, Computer Science, Data Science
-
career paths and career progression. An excellent holiday allowance of 27 days (pro rata), plus additional university closure days and bank holidays Employee Assistance Programme and Counselling Service
-
INTERNAL VACANCY This vacancy is open to employees of the University of Nottingham only. The role involves managing the Biomedical Research Centre (BRC) Gastro Theme programme including budget
-
basic biology or anatomy. Applicants must hold a full UK manual driving licence and have a minimum of GCSEs (grade C or above) in Maths and English or equivalent, or relevant experience in a similar
-
of innovative computational methods using Big Data, Behavioural Science and Machine Learning to understand behaviour through the lens of digital footprint/“smart data” datasets, cutting across sectors ranging