Sort by
Refine Your Search
-
Category
-
Program
-
Employer
- ;
- King's College London
- KINGS COLLEGE LONDON
- University of Cambridge
- ; University of Exeter
- Durham University
- University of Bath
- University of Bristol
- University of Leicester
- University of London
- University of Newcastle
- University of Nottingham
- ; University of Cambridge
- ; University of Leeds
- ; University of Leicester
- Bangor University
- Cranfield University
- DURHAM UNIVERSITY
- John Innes Centre
- Lancaster University
- Liverpool John Moores University
- University of Glasgow
- University of Greenwich
- University of Hertfordshire
- University of Leeds
- University of Lincoln
- University of Liverpool
- University of Northampton
- University of Stirling
- University of Ulster
- 20 more »
- « less
-
Field
-
information [e.g. statistics, queries, bookings for activities/events] and respond to queries which you receive. · Liaise with staff in other areas to ensure that services are being delivered in
-
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
-
of introductory social science statistics including Generalised Linear Models. A5 Knowledge of teaching methods and techniques for quantitative social science research methods. Desirable B1 Knowledge of advanced
-
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
-
knowledge in statistics and experience with AI methods, techniques, tools, and application is highly desirable. Additional information: Interviews will be held on 20 June 2024. For further information and
-
. 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
-
. Experience of working with the wider community (policymakers, regulators etc). Good statistical skills including general statistical methods. Desirable Experience in bioinformatics and/or data visualisation
-
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 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