or
Continue with FacebookLooking to list your PhD opportunities? Log in here.
We have 38 Probability PhD Projects, Programmes & Scholarships for Self-funded Students in the UK
Probability PhD Projects, Programmes & Scholarships for Self-funded Students in the UK
We have 38 Probability PhD Projects, Programmes & Scholarships for Self-funded Students in the UK
Extreme-weather prediction with Prithvi-WxC
The University of Manchester
Faculty of Humanities Doctoral Academy, Alliance Manchester Business School
The University of Manchester, funded by EPSRC and in collaboration with IBM, is offering a fully funded 4-year PhD studentship through the EPSRC Industrial Doctorate Landscape Award (IDLA). Read more
Multi-Language Statistical Classification of Natural and Computer-Generated Texts
This project concerns the statistics of written documents, whose properties are analogous to those of other type-token systems such as city populations, personal incomes and galactic superclusters. Read more
Faculty of Science URSA PhD Project: Learning with limited data for Unlearning in Large Multimodal Models
This project is one of a number that are in competition for funding from the University of Bath URSA competition, for entry in September 2025. Read more
Digital Twin Extrapolation in Space Object Re-Entry Monitoring
Project Summary. Develop advanced digital twin technology for space object re-entry monitoring, addressing multiphysics coupling and hybrid uncertainties. Read more
Last chance to apply
Fluctuations in high-dimensional random landscapes
Research Group:
Disordered Systems
High-dimensional random landscapes are important tools to model e.g. the energy functions of disordered systems, or the cost functions used in machine-learning algorithms [1]. Read more
PhD in Mechanical Engineering - Federated Digital Twins for Reducing Risk and Uncertainty in Hydrogen Integration.
The energy transition is a highly stochastic and complex problem, especially given the increasing demand to rapidly decarbonize through whole systems thinking – coupling previously independent critical infrastructure and services e.g., energy-transport networks etc. Read more
Last chance to apply
(UoM - A* STAR) Controlled Synthesis of Virtual Patient Population with Multimodal Representation Learning
In silico clinical trials (ISCTs) have become essential for simulating cardiovascular phenomena to evaluate medical interventions and devices. Read more
CDT-GIF: Material Flow Analysis to quantify national-scale decarbonisation benefits from resource efficiency
This advert will close once a suitable candidate has been found. This PhD is one of a number of projects hosted by the Centre for Doctoral Training in Green Industrial Futures (CDT-GIF). Read more
Decolonizing AI: Building Culturally Aware Multimodal AI
Building upon the NVIDIA-funded project, this project tackles the critical challenge of cultural bias in Vision-Language Models (VLMs). Current VLMs often perpetuate harmful stereotypes due to their training data. Read more
Using AI to make road fleet operations more efficient, safe, and sustainable
Road-based vehicle fleets are the cornerstone of modern-day transport and logistics systems, supporting a wide range of passenger and freight travel needs. Read more
Long time behaviour of generative models
Research Group:
Financial Mathematics
The proliferation of generative models, combined with pretraining on web-scale data, raises a crucial question. Read more
Prediction of disease onset by integrated AI approaches
Easier, accurate, and early diagnosis of diseases requires robust biomarkers. Omics approaches that measure proteins, lipids, and metabolites in a biofluid are routinely used to discover phenotypic biomarkers of diseases. Read more
Statistical foundations of deep generative models
Deep generative models (DGMs) are a broad class of models that train deep neural networks to generate synthetic samples from a target distribution associated to a given training data set. Read more
(UoM - IISc Bangalore) Beyond Traditional Models: Pricing, Hedging, and Risk Management in Complex Financial Markets
Stochastic modelling in finance presents significant challenges tied to real world complexities. With recent advances, we now have models that account for limited arbitrage, transaction costs, including volatility derivatives, and accounting for model uncertainties. Read more
Mathematically modeling systems resilient against unforeseen attacks
This project will propose mathematical decision-support tools to assist an operator in making the UK electrical grid more resilient against unforeseen attacks and develop algorithms that enable us to solve such models both efficiently and quickly. . Read more