PIPS opportunity – ITECHO HEALTH Machine Learning – Deadline: 23 October 2019

This is an opportunity to spend 3 months with ITECHO HEALTH as a Machine Learning Research Intern.

Note the tight deadline: 11:59 hours Wednesday 23rd October 2019.

About ITECHO HEALTH

Website: http://www.itechohealth.com/

Itecho Health is a young, dynamic company established to develop digital health applications in long-term or stable conditions and is led by clinicians and experts in technology and business. We have created AscelusTM – a fully integrated platform with patient and clinician user applications and AI/machine learning module interconnected with existing hospital IT systems to improve management of long-term conditions. This aims to benefit patients (increased convenience and empowerment), commissioners (reduced costs) and hospitals (increased capacity for clinicians). This approach has been proven successful in 12,000 patients with stable HIV across five hospitals in Europe. We are currently working on three main research projects:

  1. To develop our platform for use in fertility medicine – to improve fertility outcomes in sub-fertile patient populations, through personalised prescription of lifestyle factors, predominantly physical activity and exercise. The AI system will integrate patient data and NHS Trust clinical records to develop optimal lifestyle interventions and advice.
  2. To develop our platform for management of patients with Monoclonal gammopathy of undetermined significance (MGUS), that will provide a more convenient and time efficient way of managing their condition. The project aims to implement AscelusTM, allowing patients to record symptoms, receive clinical advice, test results, information on medication, and make appointments on their mobile device. This will reduce the need for face-to-face appointments and free up clinician time for more complex patients.
  3. To develop our platform to assist in the management of men with advanced prostate cancer. Men with advanced prostate cancer currently have to attend out-patients up to 15 times per year and our technology may be able to half the number of visits and replace these with a mobile interaction and video conferencing with the existing specialist team.

We are based in Nexus, a newly built research and innovation centre in the heart of the University of Leeds campus: https://www.nexus.org.uk/ 

Project background

Breakthrough advances in AI and machine learning (ML) have led to ambitious visions of how new systems can help revolutionize healthcare. These range from new approaches to understanding health risks, predicting disease progression, and creating personalized health interventions for improved patient outcomes; through to the development of innovative tools to support the practices of healthcare professionals, and reduce spending. To realize this tremendous potential requires the development of machine learning applications that are effective, trustworthy and implementable in real healthcare contexts. Itecho Health and key partners want to build a strong intelligence team to tackle this challenging ambition:– a multi-disciplinary group of machine learning researchers, social scientists, designers and engineers. As a Machine Learning Research Intern, you will be part of a team that develops human-centred machine learning solutions that can transform care pathways and improve health outcomes.

During the internship you will be working on all three project areas, with a main focus on improving and adapting the AscelusTM platform. Specifically, you will aid in the development of machine learning and AI interfaces for each project.

What you will do

During the internship you will be working on all three project areas, with a main focus on improving and adapting the AscelusTM platform. Specifically, you will aid in the development of machine learning and AI interfaces for each project.

Key roles and responsibilities:

  • Work with an interdisciplinary team around healthcare applications of machine learning.
  • Develop novel machine learning models and algorithms which consider human (e.g. clinicians, patients) interaction with these algorithms.
  • Design, implement and evaluate machine learning experiments.
  • Write-up findings in technical documents and peer-reviewed publications.
  • Present your work to a range of audiences.

Ideal candidate

The characteristics listed below are ideally required for the role.  However, if you are not sure that you match all the criteria but you are interested in the placement, please see contact details below

 to have a discussion before applying.  (Don’t delay, as it is a tight application deadline).  

  • Have knowledge of machine learning models and algorithms.
  • Be enrolled in a PhD program in the area of computer vision/machine learning, statistics, computer science or a related field.
  • Have experience/interest in healthcare.
  • Experience of disseminating work through publication and presentation.
  • Have strong programming skills.
  • Have experience in software development practices.

When

Ideally, internships will take place for 3 months, sometime between November 2019 and April 2020.  It may be possible for the dates to be flexible – Please see contact details below if you need to discuss.

Where

You will be based at the ITECHO HEALTH offices within Nexus on The University of Leeds campus, within a short walk from Leeds train station.

Nexus
Discovery Way
University of Leeds
Leeds
LS2 3AA

GET DIRECTIONS

How to apply

Deadline: 11:59 hours Wednesday 23rd October 2019

Note the tight deadline: DO NOT DELAY in applying.  

Download ITECHO HEALTH Machine Learning Intern application form HERE

Return your completed application form to:

Joanne Howorth | Engagement Manager: Talent and Skills | Nexus | Research and Innovation Service | 

Email: j.howorth@leeds.ac.uk

Tel: 0113 343 2706

Contact

For enquiries concerning the details of the placement – duties, dates, general discussion about suitability, etc – please contact Joanne Howorth as above in the first instance.  She will direct you to the relevant person to speak to in the ITECHO HEALTH team.