Reproducible Machine Learning of Wearables in Health Data Science


Join us at St Hilda's College Oxford, overlooking the River Cherwell and Christ Church Meadow, for an immersive week-long residential post-graduate short course on reproducible machine learning of wearables datasets. This course aims to connect post-graduate and post-doctoral researchers from academia and industry with experts at Oxford's Big Data Institute and Nuffield Department of Population Health.

Our friendly tutors, internationally recognised for their scientific expertise, will offer specialist instruction and hands-on computer practicals across five broad areas at the intersection of wearables, machine learning, and health data science: real world validation, time-series machine learning, reproducibility, reporting, and epidemiological considerations.

The course is aimed at trainee scientists actively engaged in health data science research, who wish to expand their knowledge of concepts and techniques.

Thanks to the generous support of Health Data Research UK, we will offer bursaries to reduce the course fee to £250 for up to 13 early career data scientists who are affiliated with UK Health Data Research Alliance members (link to list of current Alliance members)

Programme details

The inaugural course will include:

  • Daily lectures providing broad context and conceptual insights into key issues
  • Interactive computer sessions for consolidating conceptual knowledge with practical skills
  • Opportunities for one-to-one interactions with leading Oxford academics
  • A relaxed small-group atmosphere in beautiful Oxford
  • Dining and en suite accommodation at St Hilda's College
  • Exclusive use of the college bar overlooking Christ Church Meadow
  • Refreshments served during teaching breaks
  • Closing Gala dinner in a historic Oxford dining hall

The venue

Founded in 1893, St Hilda's College is located at the eastern end of the High Street Oxford, over Magdalen Bridge, and lies picturesquely on the east of the River Cherwell with views over Christ Church Meadow and Magdalen College Tower. It is named after the Anglo-Saxon Saint, Hilda of Whitby, and was the last of the women’s colleges established in Oxford, and the last to remain an all-women’s college, until 2008. St Hilda’s College reached its 125th anniversary in 2018, coinciding with its 10th year anniversary as a ‘mixed’ college that accepts both male and female students, following a supplemental charter granted in 2007. It now has almost equal numbers of men and women.

St Hilda's College gardens and grounds enjoy a unique setting stretched along the banks of the River Cherwell, looking west towards the Oxford Botanic Gardens and the historic city of Oxford. The college has its own fleet of punts, which students may use.

The college is also home to the Jacqueline Du Pré Music Building, a concert venue named after the famous cellist who was a honorary fellow of the college.


Sunday 12 March

Arrival at St Hilda's College, with registration in the afternoon, followed by an opening reception and dinner in the evening in the friendly and relaxed dining hall.

Monday 13 March

Real world validation, including an overview of reproducible machine learning in health data science, how to setup devices, ethical issues around data collection, and how to use virtual machines.

Tuesday 14 March

Time-series machine learning, covering wearable cameras, accelerometer data cleaning, and version control systems.

Wednesday 15 March

Reproducibility, specifically the use of open datasets for human activity recognition, open models for self-supervised learning, and the tools to use these e.g. PyTorch.

Thursday 16 March

Reporting machine learning models in health data science, including examples of how to do this to robustly develop and share machine learning models to measure sleep and steps from accelerometer datasets.

Friday 17 March

Epidemiological considerations, featuring bias, parallel computing of wearable phenotypes, and association with clinical outcomes.

To mark the end of the course we will have a closing drinks reception and a Gala Farewell Dinner on the Thursday evening.

Course Director and Tutors

Professor Aiden Doherty, Course Director

University of Oxford, Big Data Institute - Biography

The course will feature presentations by:

Professor Marcus Munafo,

University of Bristol - Biography

Professor Gary Collins

University of Oxford - Biography

Dr Catalina Vallejos

University of Edinburgh - Biography

Dr Maxine Mackintosh

Genomics England - Biography

Professor Derrick Bennett

University of Oxford - Biography

Dr Laura Brocklebank

UCL - Biography

Dr Scott Small

University of Oxford - Biography

Dr Shing Chan

University of Oxford - Biography

Dr Federica Lucivero

University of Oxford - Biography

Hang Yuan

University of Oxford - Biography


Participants on the course will receive a University of Oxford Certificate of Attendance.


Description Costs
All tuition, en suite room + full board, starting 12.03.23 £1750.00


Thanks to the generous support of Health Data Research UK, we will offer bursaries to reduce the course fee to £250 for up to 13 early career data scientists who are affiliated with UK Health Data Research Alliance members (link to list of current Alliance members)


Residential Programme Fees - £1,750

The fees will include:

  • All tuition
  • Full social programme 
  • Accommodation in a single en suite room in St Hilda's College with private shower and toilet for the nights of Sunday 12 March to Thursday 16 March 2023 inclusive;
  • All meals in College starting with an opening drinks reception and dinner on Sunday 12 March, and then breakfast, lunch and dinner during the week and ending with lunch on Friday 17 March 2023.
  • Weekday morning tea/coffee and biscuits

Please note the course ends at lunchtime on Friday 17 March, so participants will have accommodation for the night of Thursday 16 March and then will need to vacate their room on Friday 17 March.

Cancellations and refunds

Participants who wish to cancel must inform the Programme Administrator by emailing

Please be aware that all payments (and refunds) are subject to exchange rates at the time of processing.

The status of the course will be reviewed on 20 February 2023. If it is likely that the course may be cancelled, all participants enrolled on the course will be notified in writing within seven days, and possible options clearly explained.


We regret that we are unable to provide advice on individual visas. Students are advised to consult their closest British Embassy, Consulate or High Commission for the most up-to-date advice. Students should also refer to the University's Visa & Immigration team at or alternatively via email at: 


Applicants should send:

  • A completed application form
  • A half-page cover letter explaining how they would benefit from attending this course. Applicants should state if, and why, they should to be considered for a Health Data Research UK bursary.
  • A recent CV demonstrating their active engagement in health data science

The deadline to apply for the course is currently noon 20 February 2023. Applicants who require a UK visa are strongly encouraged to allow sufficient time for any formal visa applications to be processed. 

Please note that immediately after the deadline is closed, we will be accessing the level of interest in the course. If we decide it is not viable to run the course, participant's fees will be refunded and any other potential options will be provided. You may wish to take out travel insurance in case of any issues with your journey, or if the course may be cancelled.

You can either send the digital version of your completed application or email us a scan of your completed form. If you are having issues using Microsoft Word, you can find a .PDF version of the application form here that you can complete and scan.

Selection criteria

This course is aimed at early career health data scientists as well as post-graduate and post-doctoral researchers, so applicants should have at minimum a bachelors’ degree and be currently engaged in health data research

If you have any queries about this, please email the course administrator at

IT requirements

It is expected that participants will bring their own laptops to participate in the computer practicals, although limited spare laptops are available in case of any emergencies.