Sort by
Refine Your Search
-
beyond. Your tasks will be to lead data reduction, analysis and modelling of GRAVITY+ data and contribute to the development of the data reduction software. The Southampton Astronomy Group provides a
-
, ranging from AI to novel geometry modelling techniques. While this position is initially for a fixed term period, depending on the success of the role, opportunities will be explored to extend it beyond
-
digital design technologies, ranging from AI to novel geometry modelling techniques. While this position is initially for a fixed term period, depending on the success of the role, opportunities will be
-
materials characterization tools; computational multi-physics/electromagnetics modelling and eigenmode analysis for photonic crystals; terahertz far-field spectra measurements or near-field scanning
-
preliminary data, it combines mechanistic and translational immunology with bespoke in vivo models to define and exploit therapeutically relevant subsets. The Research Fellow will lead studies on cytotoxic T
-
for precision targeting of AML, an aggressive leukaemia with poor survival outcomes. Building on strong preliminary data, it combines mechanistic and translational immunology with bespoke in vivo models to define
-
An opportunity has arisen for a Research Fellow to join the Faculty of Medicine, School of Human Development and Health based at Southampton University Hospital Trust (Southampton General Hospital
-
modelling and eigenmode analysis for photonic crystals; terahertz far-field spectra measurements or near-field scanning spectroscopy. In this role, you will join an interdisciplinary research group
-
statistical, machine learning, and artificial intelligence (AI) techniques to analyse 'omics and clinical data, and contributing to the development of biomarkers and predictive models. A critical part of your
-
to the development of biomarkers and predictive models. A critical part of your role will be to ensure all data and workflows are reproducible and shareable, aligning with our 'data lake to discovery' approach under