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Nikos Nikolaou

1 year ago

Data Intensive Science UCL (University College London) in United Kingdom

Degree Level

PhD

Field of study

Machine Learning

Funding

Full funding available

Deadline

December 31, 2026
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Country

United Kingdom

University

University Name
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Where to contact

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Keywords

Machine Learning
Artificial Intelligence
Astrophysics
Molecular Physics
Cosmology
Exoplanetology
Protein Dynamics
Pharmaceutic
Physics

About this position

Does the prospect of advancing Physics research by mastering the latest advancements in Machine Learning / Artificial Intelligence (ML/AI) seem exciting? If so, then apply now for a place in the September 2025 cohort of UCL 's CDT in Data Intensive Science! We offer a 4-year PhD programme, at the intersection of ML/AI & Physics, with several training and industrial placement opportunities!

I am offering 3 projects:
1) Causal Representation Learning in Astrophysics and beyond
(applications: Cosmology, Exoplanetary Science), with Prof. Ofer Lahav

2) Exotic forms of matter interaction of modules with intense laser pulses and machine learning techniques for efficient prediction of ultrafast phenomena
(application: Molecular Physics), with Prof. Agapi Emmanouilidou

3) Discovering causal relationships governing biomolecular dynamics
(application: Biomolecular Dynamics, Pharmaceutics), with Prof. Edina Rosta

Details for all available projects can be found here: https://lnkd.in/ghKZXzxJ

If any of this interests you, apply now, or reach out to us for any questions!
https://lnkd.in/ewVqT3FF

Deadline: January 10th (International students) / January 27th (Home students)

UCL Centre for Data Intensive Science and Industry
ai ml machinelearning artificialintelligence physics
astronomy cosmology galaxies exoplanets ultrafastmoleculardynamics
biomoleculardynamics , pharmaceutics , pharma
phd phdposition

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

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