PhD Data Science
Our PhD Data Science is an advanced research degree within our Department of Mathematical Sciences and we have staff members available to act as supervisors across a number of areas within data science. Possible areas of research include: artificial intelligence, classification/supervised learning, clustering/unsupervised learning, data science education, deep learning, industry 4.0, information retrieval, mathematical foundations of data science, multidimensional scaling, optimisation, and statistical learning. If you’re interested in doing a data science research degree at Essex, contact our Department to discuss potential research areas.
Our staff are strongly committed to excellence in research and excellence in education. Our Department of Mathematical Sciences (DMS) and our School and Computer Science and Electronic Engineering (CSEE) have introduced undergraduates and postgraduate courses in data science since 2014.
The University of Essex is a leading institution worldwide on Data Science Education. DMS has strong track record on Knowledge Transfer Partnerships (KTP) with data-driven industries, for example: Profusion, Mondaq, MSXI and Ocado. DMS has two research groups: Data Science and Mathematics.
Our Department of Mathematical Sciences is genuinely innovative and student-focused. Our research groups are working on a broad range of collaborative areas tackling real-world issues. Here are a few examples:
- Our data scientists carefully consider how not to lie, and how not to get lied to with data. Interpreting data correctly is especially important because much of our data science research is applied directly or indirectly to social policies, including health, care and education.
- We do practical research with financial data (for example, assessing the risk of collapse of the UK’s banking system) as well as theoretical research in financial instruments such as insurance policies or asset portfolios.
- We also research how physical processes develop in time and space. Applications of this range from modelling epilepsy to modelling electronic cables.
- Our optimisation experts work out how to do the same job with less resource, or how to do more with the same resource.
- Our pure maths group are currently working on two new funded projects entitled ‘Machine learning for recognising tangled 3D objects’ and ‘Searching for gems in the landscape of cyclically presented groups’.
- We also do research into mathematical education and use exciting technologies such as electroencephalography or eye tracking to measure exactly what a learner is feeling. Our research aims to encourage the implementation of ‘the four Cs’ of modern education, which are critical thinking, communication, collaboration, and creativity.
Our PhD Data Science is an advanced research degree within our Department of Mathematical Sciences and we have staff members available to act as supervisors across a number of areas within data science. Possible areas of research include: artificial intelligence, classification/supervised learning, clustering/unsupervised learning, data science education, deep learning, industry 4.0, information retrieval, mathematical foundations of data science, multidimensional scaling, optimisation, and statistical learning. If you’re interested in doing a data science research degree at Essex, contact our Department to discuss potential research areas.
Our staff are strongly committed to excellence in research and excellence in education. Our Department of Mathematical Sciences (DMS) and our School and Computer Science and Electronic Engineering (CSEE) have introduced undergraduates and postgraduate courses in data science since 2014.
The University of Essex is a leading institution worldwide on Data Science Education. DMS has strong track record on Knowledge Transfer Partnerships (KTP) with data-driven industries, for example: Profusion, Mondaq, MSXI and Ocado. DMS has two research groups: Data Science and Mathematics.
Our Department of Mathematical Sciences is genuinely innovative and student-focused. Our research groups are working on a broad range of collaborative areas tackling real-world issues. Here are a few examples:
- Our data scientists carefully consider how not to lie, and how not to get lied to with data. Interpreting data correctly is especially important because much of our data science research is applied directly or indirectly to social policies, including health, care and education.
- We do practical research with financial data (for example, assessing the risk of collapse of the UK’s banking system) as well as theoretical research in financial instruments such as insurance policies or asset portfolios.
- We also research how physical processes develop in time and space. Applications of this range from modelling epilepsy to modelling electronic cables.
- Our optimisation experts work out how to do the same job with less resource, or how to do more with the same resource.
- Our pure maths group are currently working on two new funded projects entitled ‘Machine learning for recognising tangled 3D objects’ and ‘Searching for gems in the landscape of cyclically presented groups’.
- We also do research into mathematical education and use exciting technologies such as electroencephalography or eye tracking to measure exactly what a learner is feeling. Our research aims to encourage the implementation of ‘the four Cs’ of modern education, which are critical thinking, communication, collaboration, and creativity.
