223 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "University of Warwick" positions at King's College London in United Kingdom
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
an exciting opportunity for a Postdoctoral Research Associate to join their dynamic, interdisciplinary team to shape how multimodal bioimaging data is stored, shared and reused. The Parsons Group is based in
-
or similar areas of work (e.g. contracting, business development, operation support, finance/accounting etc.) Experience and/or knowledge of using databases, management information systems and Excel Experience
-
grade 7. Visit the Centre for Research Staff Development for more information. About You To be successful in this role, we are looking for candidates to have the following skills and experience
-
. This role is based within the Faculty of Life Sciences and Medicine, in the Department of Infectious Diseases, which brings together expertise across microbiology, immunology, clinical sciences, data science
-
information clearly, both orally and in writing. Present research findings to academic and public audiences. Teamwork and Collaboration Work closely with other team members on shared areas of interest
-
Teaching Technicians, Teaching Fellows and AEP equivalent up to and including grade 7. Visit the Centre for Research Staff Development for more information.
-
Technicians, Teaching Fellows and AEP equivalent up to and including grade 7. Visit the Centre for Research Staff Development for more information. About You To be successful in this role, we are looking
-
-design workshops, interviews, requirements gathering, data curation/annotation activities, and contribute to the design and evaluation of human–computer interface prototypes through design sprints and
-
Description Full details of the role and the skills, knowledge and experience required can be found in the Job Description document, provided at the bottom of the page. This document will provide information
-
’ to ablate. Here, we aim to further develop, clinically validate, and prospectively evaluate, a novel in-silico tool that uses patient imaging data to reconstruct personalised ‘digital twin’ cardiac models