牛津大学

Health Data Science

项目介绍

About the course

The Oxford EPSRC CDT in Health Data Science offers opportunities for doctoral study in computational statistics, machine learning and data engineering within the context of ethically-responsible health research. 

The Oxford EPSRC Centre for Doctoral Training (CDT) in Health Data Science offers a four-year doctoral programme, beginning with the training year, which consists of two terms of intensive training in core data science principles and techniques followed by a third term where students undertake two 8-week research placements in two of their chosen research areas. It is expected that one of these projects will become the basis of the student’s doctoral research, carried out in the following three years. Taught modules and subsequent research supervision are provided by leading academics from the departments of Computer Science (the host department), Statistics, Engineering Science, the Nuffield Department of Medicine, and the Nuffield Department of Population Health.

The first year taught modules include:

  • Ethics of Health Data Science
  • Introduction to Computational Statistics
  • Modern Statistical Methods
  • Bayesian Modelling
  • Introduction to Machine Learning
  • Machine Learning Topics
  • Deep learning, Databases
  • Data Modelling
  • Process Modelling
  • Data Governance
  • Wearables
  • Medical Image Analysis
  • Epidemiology and Clinical Trials
  • Genetics
  • Infectious Disease Epidemiology
  • Pathogen Evolution and Phylodynamics.

A typical weekly timetable contains morning lectures from 9am to 12pm, followed by an afternoon of practical computational exercises from 1pm until 4pm.

Each term of taught modules concludes with an extended, team-based two-week data challenge where the cohort uses an at-scale data set to address a current health research area. Our data science challenges involve engagement from industry and healthcare partners such as The British Heart Foundation, NVIDIA and exchange students from our partner institutions in Berlin.

The centre is based in the Oxford Big Data Institute. The institute is an analytical hub for multi-disciplinary working at Oxford, connecting world-leading expertise in statistics, computer science, and engineering to data-driven research in medicine and population health. It is also home to the newly established Wellcome Centre for Ethics and Humanities.

The institute houses internationally recognised research groups in genomic medicine, medical image analysis, mobile and sensor data, infectious diseases, large-scale clinical trials, ethical aspects of healthcare delivery and the ethics of health research.

Research groups in partner departments address related challenges in data science: machine learning, knowledge representation, healthcare economics and cyber security.

Supervision

The allocation of graduate supervision is the responsibility of the Centre for Doctoral Training and it is not always possible to accommodate the preferences of incoming graduate students to work with a particular member of staff.

Each student will benefit from dual supervision for the duration of their research project, with at least one of the two supervisors having a strong background in core data science. Many students will wish to pursue a project in collaboration with a partner organisation: a technology company such as Elsevier, NVIDIA, Perspectum Diagnostics, or Zegami; one of our pharmaceutical partners such as GSK, UCB, or Novartis; other groups such as the NIHR Oxford Biomedical Research Centre or the Cancer Research UK Oxford Centre, as well as the research teams in the Medical Science Division provide unique collaboration opportunities.

Assessment

Modules are assessed in different ways, though usually through project work. Data Challenges are assessed through group presentations on the final day of the Data Challenge. Research placements are assessed with a written report.  Health Data Ethics is a core part of the curriculum and the doctoral dissertation. During the first year ethics will be assessed by presentation. Students will be asked to provide a short presentation of the ethical issues arising in each of their third term placements.

Graduate destinations

This is a new course and there are no alumni yet. It is expected that graduates will be well placed to take on leading roles in industry, academia and the public sector. 

Changes to this course and your supervision

The University will seek to deliver this course in accordance with the description set out in this course page. However, there may be situations in which it is desirable or necessary for the University to make changes in course provision, either before or after registration. The safety of students, staff and visitors is paramount and major changes to delivery or services may have to be made in circumstances of a pandemic (including Covid-19), epidemic or local health emergency. In addition, in certain circumstances, for example due to visa difficulties or because the health needs of students cannot be met, it may be necessary to make adjustments to course requirements for international study.

Where possible your academic supervisor will not change for the duration of your course. However, it may be necessary to assign a new academic supervisor during the course of study or before registration for reasons which might include illness, sabbatical leave, parental leave or change in employment.

For further information please see our page on changes to courses and the provisions of the student contract regarding changes to courses.

录取要求

  • a first-class or strong upper second-class undergraduate degree with honours in a data science subject.
  • A previous master’s degree is recommended, but not essential.

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牛津大学

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牛津大学位于英国牛津,世界顶尖的公立研究型大学,采用书院联邦制。
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联系方式

电话: +44 1865 270000

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