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We have 177 Computational Physics PhD Projects, Programmes & Scholarships for Self-funded Students






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Computational Physics PhD Projects, Programmes & Scholarships for Self-funded Students

We have 177 Computational Physics PhD Projects, Programmes & Scholarships for Self-funded Students

A PhD in Computational Physics involves the development of mathematical models and computer programmes that can compute the behaviour of physical systems.

What's it like to study a PhD in Computational Physics?

A PhD in Computational Physics requires the development of new mathematical models and computer programmes. This can involve working on problems in areas like:

  • quantum many-body theory
  • computational fluid dynamics
  • biophysical simulation
  • neutron transport
  • beam simulation

You'll be encouraged to work independently on your research topic, which will usually be part of a larger project being led by a member of staff or a research group.

In a typical Computational Physics PhD, you'll work under the guidance of an expert supervisor to whom you'll submit a thesis at the end of your study. You may also be asked to give occasional presentations about your research at departmental level.

Some Computational Physics PhDs will require laboratory-based research, but many are entirely computational.

Typical entry requirements for a PhD in Computational Physics are a 2:1 in Physics, Mathematics or a related subject, although a Masters may occasionally be required.

PhD in Computational Physics funding options

Most PhDs in Computational Physics are funded by the Science and Technology Facilities Council (STFC), meaning that you'll receive a tax-free salary along with training during your PhD.

Some universities may also offer their own funding options. If you are considering a PhD that is fully self-funded, it is advisable to confirm that the programme meets UK academic standards before you apply.

PhD in Computational Physics careers

There is a huge demand for experts in Computational Physics, with careers available in academia, finance and technology. Many Computational Physics PhD graduates also choose to become teachers.

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Last chance to apply

Magnetic resonance imaging of intrabdominal lymphatics and vasculature in Inflammatory Bowel Disease

Applications are invited for a PhD project funded by an investigator-initiated grant awarded to Prof Gordon W. Moran. MagnetiC ResOnance ImagiNg of intrabdominal lymphatiCs and vasculaturE as measures of disease activity in Ozanimod-treated patients with active UlceratIVE Colitis (CONCEIVE). Read more

Probing the star-forming ISM with fine structure lines

Supersonic turbulent motions are thought to play a major role in the star formation process in galaxies.  Theories have suggested that turbulence is responsible for shaping the interstellar medium (ISM), regulating star formation, and even setting the masses of stars as they form in young clusters. Read more

Designing tests for the identification of Quantum Spin Liquids

Quantum spin liquids (QSLs) are highly entangled low temperature states of magnetic systems. They are of fundamental importance as quantum states of matter firmly outside of conventional paradigms, having excitations with fractional quantum numbers and being described by emergent gauge theories. Read more

Using Robotics to Remove the Harmful Effects of Toxic Metals in Industrially Relevant Metal-Catalysed Processes

Organometallic catalysis is one of the most vibrant and essential areas worldwide in scientific research, with impact in a broad range of industrially relevant fields such as pharmaceuticals, agrochemicals and materials. Read more

Optimisation of radiation health monitoring through machine learning and data fusion

This PhD will combine AI (artificial intelligence) and experimental methods to provide an informed assessment of delayed material dosimetry within the radiation health monitoring landscape. Read more

Neuromorphic devices based on oxidation-conversion of van-der-Waals semiconductors

Why this research is important. Taking inspiration from the human brain, neuromorphic systems uses physics of materials and devices to process unstructured and noisy analogue data, leading to a fundamentally new approach to computing. Read more

Characterisation of tissue microstructure from non-invasive MRI using Machine Learning

The characterisation of biological tissue microstructure in vivo and non-invasively is of outmost interest in science. If successful, it could reveal unique insights into biological processes, including aging and cancer. Read more

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