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DISCnet Cohort 2023

Our students are exceptional problem solvers and highly-skilled data specialists.

From their PhD research they bring extensive experience of handling intensive tasks and managing complex data sets and problems to industry placements.

Meet The Students

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University of Sussex

Simulations of structure formation and feedback at high-redshift

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University of Sussex

Exploring the Universe on large scales with Dark Energy Spectroscopic Instrument (DESI)

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Oscar Chow

Queen Mary University London

Neutrino Oscillations in NOvA and DUNE

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Patrick Hurley

University of Sussex 

Precision LHC Phenomenology

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Chris Sorrell

Open University

I can't believe it's not JWST

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Saashiv Valjee

Queen Mary University London

Dark Matter searches with the ATLAS detector

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Mohammad Waris

Queen Mary University London

New measurement of weak mixing angle

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Jessica Copeland

University of Hertfordshire 

The coldest observed extrasolar atmospheres with JWST

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Dhariya Kataria

University of Hertfordshire

The impact of supermassive black holes on their galaxies and environment

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Jessica Pilling

University of Sussex

Cosmology with clusters of Galaxies: applications of the XMM Cluster Survey to eROSITA

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Arwa Abdulghafour

University of Sussex

Cosmology with Clusters of Galaxies: applications of the XMM Cluster Survey to the Rubin Legacy Survey of Space and Time

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Sam Philipsborn

University of Sussex

Constraining dark matter models with Euclid, LSST and 4MOST

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Darcy Peake

University of Sussex

Jet physics for the LHC and beyond

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Jocelyn Richardson

Queen Mary University London

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DISCnet is the Data Intensive Science Centre in SEPnet, and an STFC Centre for Doctoral Training;  

a collaboration between the University of Sussex, Queen Mary University of London, and The Open University

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