-
practice of Open Science principles (e.g. data sharing, code sharing, public engagement and awareness). Self-motivated, proactive, and takes initiative to problem-solve Understanding of anxiety and
-
practice of Open Science principles (e.g. data sharing, code sharing, public engagement and awareness). Self-motivated, proactive, and takes initiative to problem-solve Understanding of anxiety and
-
experience: Essential criteria PhD in computer science, AI or related area Proven experience of knowledge engineering and semantic technologies such as knowledge graphs, ontologies, data modelling, RDF, RDFS
-
reduction. You will be supported by a multidisciplinary internationally renowned team from within QMUL and the wider CD3 community which has expertise in health data science, risk prediction, statistics, AI
-
experience: Essential criteria 1. PhD in computer science, AI or related area 2. Proven experience of knowledge engineering and semantic technologies such as knowledge graphs, ontologies, data
-
robotics, mechanical engineering or a similar engineering field. The job requires an in-depth knowledge about soft inflatable/eversion robotics, sensor data acquisition and processing, computer and system
-
You will have a PhD in Computer Science or a related discipline or will have obtained it by commencement of the position. Successful candidates will have experience of model training methodologies
-
(Dr Daniel Wilson, Dr Maxie Roessler). Applicants should have a PhD in synthetic chemistry, ideally with extensive experience in handling air- and moisture-sensitive materials using Schlenk line and
-
. Machine learning/atmospheric science/satellite data processing experience preferred but not required Creative problem-solving skills and ability to work independently *Candidates with a PhD in other
-
working under pressure For further information about this position and to apply, visit http://jobs.sgul.ac.uk . The School of Health and Medical Sciences is committed to promoting equality, diversity and