PhD Data Science - Data Science Degree

Program Overview

The University of Essex's PhD Data Science program equips students with advanced skills in data science, emphasizing real-world problem-solving and big data applications. The program offers both Integrated PhD (with a Masters-level qualification) and standard PhD options, with a curriculum that includes core modules in mathematics, statistics, machine learning, data visualization, and research skills. Graduates are highly sought after in various sectors due to the high demand for data science expertise.

Program Outline

Degree Overview:

The PhD Data Science program at the University of Essex is a full-time, 4-5 year program designed to equip students with the skills and knowledge necessary to become leading data scientists. The program emphasizes the application of data science techniques to real-world problems and applications, particularly in the realm of big data. The program's objectives include:

• Developing a deep understanding of mathematical foundations of data science.
• Mastering statistical techniques and methods for data interpretation.
• Gaining proficiency in using smart devices efficiently.
• Cultivating the ability to solve real-world problems using data science.
The program offers both an Integrated PhD, which includes a Masters-level qualification in the first year, and a standard PhD, which can be pursued full-time (3-4 years) or part-time (6-7 years).

Outline:

Year 1:

• Component 03: COMPULSORY
• Applied Regression and Experimental Data Analysis (15 CREDITS):
This module focuses on applying regression models to data analysis, exploring underlying assumptions, and utilizing matrices. It covers ANOVA for normally distributed data, experimental design, nonlinear regression, generalized regression, and multidimensional contingency tables.
• Component 04: COMPULSORY
• Applied Statistics (15 CREDITS):
This module covers three application areas of statistics: multivariate methods, demography and epidemiology, and sampling. Students learn to apply and assess these methods in various situations.
• Component 05: COMPULSORY
• Machine Learning (15 CREDITS):
This module explores the principles and applications of machine learning, focusing on learning algorithms from sets of examples. It covers topics like optical character recognition, dictation software, language translators, and fraud detection.
• Component 06: COMPULSORY
• Component 07: COMPULSORY
• Research Skills and Employability (0 CREDITS):
This module helps students develop transferable skills, explore career directions, and prepare for the application process.

Year 2 - Year 4/5:

• Research: The research element of the PhD is not structured with taught modules, allowing students to delve deeply into their chosen topic and generate new knowledge.

Assessment:

• Taught Modules: Assessment is based on written examinations, practical work, and coursework.
• Dissertation: The PhD culminates in a dissertation that makes a significant contribution to knowledge.
The dissertation is defended in an oral examination (viva) with two examiners, at least one from outside Essex.

Teaching:

• Research-led Teaching: The program's curriculum is continually evolving to reflect the latest challenges and breakthroughs in the field.
• Faculty: The program boasts a team of expert faculty members specializing in various areas of data science and analytics, including machine learning, adaptation, semantic information extraction, biostatistics, data mining, actuarial mathematics, and more.
• Supervision: PhD students are encouraged to meet regularly with their supervisors.
Joint supervision across other Essex departments and schools is possible.

Careers:

• High Demand: There is a high demand for data science experts in all sectors of the economy, making graduates highly sought after in the UK and abroad.
• Career Paths: Graduates find employment in various fields, including financial services, scientific computation, decision-making support, government, risk assessment, statistics, education, and more.
• Industry Links: The program has active links with industry to broaden employment potential and placement opportunities.
• Alumni Success: Graduates have gone on to work as data scientists and data analysts in both the private and public sectors.

Other:

• Proficio Scheme: All University of Essex research students have access to the Proficio scheme, which provides training courses and funding for conference attendance and external training.
• Facilities: The School of Mathematics, Statistics and Actuarial Science is housed in the University's STEM Centre, equipped with state-of-the-art computers, software, and specialist facilities for research in areas like brain-computer interfaces, robotics, and optoelectronics.
• Collaborations: The program benefits from collaborations with the Institute of Analytics and Data Science (IADS), the ESRC Business and Local Government (BLoG) Data Research Centre, the UK Data Archive, and the Institute for Social and Economic Research (ISER).
• Knowledge Transfer Partnerships (KTP): The University has a strong track record of KTPs with data-driven industries, including Profusion, Mondaq, MSXI, and Ocado.

Home/UK fee £4,786 per year International fee £18,750 per year Fees will increase for each academic year of study.