Sort by
Refine Your Search
-
Listed
-
Employer
- University of Birmingham
- ;
- Nature Careers
- University of Nottingham
- Queen's University Belfast
- Queen's University Belfast;
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- UNIVERSITY OF MELBOURNE
- UNIVERSITY OF SURREY
- UNIVERSITY OF SOUTHAMPTON
- Birmingham City University
- CRANFIELD UNIVERSITY
- Imperial College London
- King's College London
- UNIVERSITY OF GREENWICH
- University of Cambridge
- University of Glasgow
- University of Greenwich
- University of Stirling
- 9 more »
- « less
-
Field
-
data using appropriate theoretical and methodological frameworks Apply knowledge in a way that develops new intellectual understanding Disseminate research findings through academic publications
-
Specification Hold or be close to obtaining PhD in theoretical physics or related area High level analytical capability Ability to communicate complex information clearly Fluency in relevant models, techniques
-
Collect research data via experiments carried out on the analysis and recycling of Li ion battery materials Supervise students on research related work and provide guidance to PhD students on the Li ion
-
experimental and analytical capability Ability to communicate complex information clearly Fluency in relevant modelling tools, techniques or methods and ability to contribute to developing new ones Ability
-
Collect research data via experiments carried out on the analysis and recycling of Li ion battery materials Supervise students on research related work and provide guidance to PhD students on the Li ion
-
or equivalent qualifications High level analytical capability including experience processing large media text data sets Ability to communicate complex information clearly such as publishing in political
-
internal and external partners/professionals Specialist knowledge & experience of quantitative research methods and analysing data from a range of sources Competence in analytic/statistical software such as
-
annotation of these metabolomes using multistage fragmentation (MSⁿ) data, incorporating novel computational methods and strategies (e.g. spectral matching, network-based approaches, machine learning) where
-
and healthcare system simulation modelling will be useful for evaluating these options. To that end, this team will develop a novel analytical simulation framework and use it to address these pressing
-
part of a broader collaborative team, under the supervision of Dr Shivani Pasricha, you'll utilise advanced molecular genetic technologies like CRISPR and data analytics to understand infection dynamics