Sort by
Refine Your Search
-
Category
-
Program
-
Employer
- King's College London
- University of London
- ;
- Bangor University
- Durham University
- John Innes Centre
- KINGS COLLEGE LONDON
- University College London
- University of Glasgow
- University of Hertfordshire
- University of Leicester
- University of Oxford
- University of Sheffield
- University of Stirling
- 4 more »
- « less
-
Field
-
remotely). You will have or be close to the completion of a PhD or equivalent in computational sciences (Mathematics, Engineering, Computer Science, Statistics), together with relevant research experience
-
generalisability compared to traditional adaptive control methods. Rigorous theoretical and statistical analysis will be carried out to prove the effectiveness of these proposed techniques. Hence, a strong
-
, with a relevant PhD is desirable: Interacting particle systems for Monte Carlo methods and rare event simulation Statistical physics for transport modelling Branching structures and or stochastic
-
partnership to achieve excellence in public and global health research, education and translation of knowledge into policy and practice. We are seeking a statistical modeller with an interest in climate
-
they are based on mathematical and statistical principles dating from the 1970s. Developing these pharmacometric models remains a laborious task where highly qualified staff spend large amounts of time. Aims
-
. The main focus of Centre for Advanced Cardiovascular Imaging is to apply statistical, multi-omics and machine learning approaches to national-scale imaging studies. About Queen Mary At Queen Mary University
-
statistical methods to analyse large-scale genomic datasets and decipher evolutionary patterns. Perform wet-lab experiments aimed at validating cell-diversity. Collaborate with multidisciplinary teams
-
the water system. The Role We are seeking an experienced and highly motivated Research Fellow with a strong data and statistics background to support LPIP/FORTH2O in building a world-leading data and digital
-
, with a dedication to supporting high-quality work. Strong academic background with a degree in computer science, statistics, physics, engineering, mathematics, or related fields. Proficient in Python
-
of designing and developing tools to help curate and analyse imaging data. 5. Strong grasp of univariate and multivariate statistical analyses 6. Strong programming skills (e.g., Python, r, Bash