We have 29 Probability PhD Projects, Programmes & Scholarships

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Probability PhD Projects, Programmes & Scholarships

We have 29 Probability PhD Projects, Programmes & Scholarships

A PhD in Probability offers an exciting opportunity to delve deep into the fascinating world of uncertainty and randomness. It is a field that has applications in various industries, from finance and insurance to computer science and engineering.

What's it like to study a PhD in Probability?

Studying a PhD in Probability allows you to explore the intricacies of chance and uncertainty. You will have the opportunity to work on cutting-edge research projects, developing new theories and techniques to understand and model random phenomena. From analyzing the behavior of complex systems to predicting the likelihood of events, your research will contribute to advancing the field of Probability.

During your PhD, you will work closely with your supervisor and other experts in the field. You will attend seminars, conferences, and workshops to stay updated with the latest developments and collaborate with fellow researchers. The program will also provide you with the opportunity to teach undergraduate students, enhancing your communication and presentation skills.

Entry requirements for a PhD in Probability

To pursue a PhD in Probability, you will typically need a strong background in Mathematics, preferably with a specialization in Probability or Statistics. Most universities require a minimum of a 2.1 Honours degree or equivalent, although some may consider applicants with a lower grade if they demonstrate exceptional potential. Additionally, having a Master's degree in a related field can be advantageous.

PhD in Probability funding options

Funding for PhDs in Probability may be available from various sources, including governments, universities and charities, business or industry. See our full guides to PhD funding for more information.

PhD in Probability careers

A PhD in Probability opens up a wide range of career opportunities. Many graduates go on to become researchers and professors in academia, contributing to the advancement of Probability theory and teaching the subject to future generations. Others find employment in industries such as finance, insurance, data science, and risk analysis, where the ability to understand and quantify uncertainty is highly valued.

In the financial sector, for example, your expertise in Probability can be applied to pricing derivatives, managing investment portfolios, and assessing risk. In the field of data science, you can contribute to developing algorithms and models that analyze and predict patterns in large datasets. The skills and knowledge gained during your PhD will equip you with a strong foundation to excel in various quantitative roles.

Embarking on a PhD in Probability is not only intellectually stimulating but also opens doors to a rewarding and impactful career. Whether you choose to pursue a career in academia or industry, your expertise in Probability will be highly sought after, making you a valuable asset in a world where uncertainty is ever-present.

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Untangling Minor Planet Families

The Japan/New Zealand/US Microlensing Observations in Astrophysics (MOA) collaboration has been engaged with the detection of exoplanets via gravitational microlensing of over 25 years. Read more

Hybrid OFDM transmission system for connected autonomous vehicles

Orthogonal Frequency Division Multiplexing (OFDM) is a technique that exploits orthogonal carriers to transmit information and enhance received signal diversity and consequently increase received signal-to-noise ratio (SNR). Read more
Last chance to apply

Nose-to-tail emulation with nested sampling for online decision-making

The UKRI AI Centre for Doctoral Training (CDT) in Decision Making for Complex Systems is a joint CDT between The University of Manchester and the University of Cambridge. Read more

PhD Studentship in Efficient and Reliable Probabilistic Machine Learning

One fully funded PhD positions to work with Dr Antonio Vergari in the School of Informatics at the University of Edinburgh, on projects in the research areas of Probabilistic Machine Learning, Neuro-Symbolic AI and Deep Generative Models. Read more
Last chance to apply

Learning theory and methods for novel types of distributional shifts

The UKRI AI Centre for Doctoral Training (CDT) in Decision Making for Complex Systems is a joint CDT between The University of Manchester and the University of Cambridge. Read more
Last chance to apply

Human-in-the-loop Generative Models for Experimental Design

The UKRI AI Centre for Doctoral Training (CDT) in Decision Making for Complex Systems is a joint CDT between The University of Manchester and the University of Cambridge. Read more

Optimal dividend and capital injection with practice constraints and risk management restrictions

The optimal dividend problem is a hot research topic in the field of actuarial and financial mathematics. How to design a dividend strategy that is consistent with the company’s current risk management objective and suitable for the practical operating constraints is an important problem in practice. Read more

Extreme Value Analysis of Certain Risk Models

Based on the extreme value analysis theory, this project will build some widely recognized risk models, discuss the relevant financial risk measurement indices, and analyze the calculation and properties of these indices. Read more

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