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DISCnet Cohort 2021

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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Anisa Aubin

University of Sussex

Working on Simfarm2030: An empirical, data driven, model for wheat cultivars and optimisation for future climate scenarios.


Mauricio A. Diaz

University of Southampton

Machine Learning & Artificial Intelligence for BSM Phenomenology 


Jussi Kuusisto

University of Sussex

Exploring Galaxy Formation in the Distant Universe with Hydrodynamical Simulations and Next Generation Space Telescopes"


Francisco Martínez López

Queen Mary University London

Data Acquisition and Dark Matter studies at the DUNE FD.


Callum Boocock

Queen Mary University London

Magnetohydrodynamic Waves in Realistic 3D Solar Atmospheric Structures

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Lewis Hill

University of Portsmouth

Stellar Populations in Galaxies with the Large Galaxy Survey SDSS IV/MaNGA".

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Joshua Wilde

The Open University

Using convolutional neural networks to identify gravitational lenses and working on interpreting these networks

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Giorgio Cerro

University of Southampton

Machine learning for particles jets


Arran Freegard

University of Southampton

Exploring Dark Matter signals and their backgrounds with ATLAS at the LHC


David Turner

University of Sussex

From Cluster Mass Calibration to Cluster Cosmology


Jacob Orwat-Kapola

University of Southampton

Data science and machine learning applied to problems at the intersection of observational astronomy and the industry


Adam McMaster

The Open University

Searching for black holes and variable stars in archival data from the SuperWASP survey, with help from citizen scientists and machine learning.

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Ryan Wood

University of Sussex

Jet Physics at the Large Hadron Collider in and beyond the Standard Model.

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Maria Del Carmen Campos Varillas

University of Sussex

Galaxy evolution: statistical analysis of data within the Herschel Extragalactic Legacy Project (HELP) 

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