Research Associate in Medical Statistics

3 days ago

Manchester, United Kingdom The University of Manchester Full time

We are seeking a Research Associate in Medical Statistics to join a project entitled “CONNECT: Digital markers to predict psychosis relapse”. This project will recruit individuals with psychosis, and use smart phone apps to collect passive and active data using a prospective observational cohort study design. We will use this data to develop and validate a personalised risk prediction algorithm for relapse. Additionally, we want to maximise engagement and information obtained from digital remote monitoring by asking the right questions, at the right frequency and time.

The post holder’s main duty will be to provide statistical expertise in the study, with responsibility for:

- Development, and validation, of a risk prediction model for relapse. Using data from the prospective study, you will develop/train a risk prediction model that can be used to identify patients at risk of relapse. This will use data from a variety of sources including symptoms recorded in real-time through a mobile phone app, and passively collected data such as geolocation. The model will be dynamic (updating predictions as patients record new data), and will consider statistical and machine learning algorithms.
- Development of statistical methods for adaptive sampling. At present, we collect real-time data from patients at regular intervals. We would like the digital system to monitor user data in real-time and learn to dynamically adjust the sampling frequency. For example, changes in patterns of behaviour from passive data may be an early warning of deteriorating symptoms and can be used by adaptive sampling models to increase the frequency of symptom collection. Frequency can be reduced if a person appears to be stable and well. You will investigate methodology to allow this, and investigate/compare them using the data from the CONNECT study.

You should have a PhD (or equivalent) in statistics or a similar field, and be developing your publication record. You should have specific skills and expertise in statistical modelling and/or machine learning.

**What you will get in return**:

- Fantastic market leading Pension scheme
- Excellent employee health and wellbeing services including an Employee Assistance Programme
- Exceptional starting annual leave entitlement, plus bank holidays
- Additional paid closure over the Christmas period
- Local and national discounts at a range of major retailers

Our University is positive about flexible working you can find out more here

Hybrid working arrangements may be considered.

**Enquiries about the vacancy, shortlisting and interviews**:
Name: Dr Glen Martin

**General enquiries**:
**Technical support**:
**Please see the link below for the Further Particulars document which contains the person specification criteria.

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