Leveraging Electronic Health Records: Bayesian Joint Longitudinal and Survival Modelling of Bivariate Longitudinal Trajectories for Two Disease Outcomes

Overview

We are thrilled to announce an exceptional PhD opportunity in medical statistics with machine learning, specifically tailored for Electronic Health Records and Big Data analysis. This project is designed for candidates eager to explore and expand the realms of statistical analysis and reliable machine learning, with a special emphasis on joint longitudinal and time-to-event data modelling.

Key Research Areas

The successful candidate will embark on a journey of discovery and innovation in several key areas:

Bayesian Joint Longitudinal and Survival Modelling for EHR Data:

·      Investigate Existing Bayesian Frameworks:

Explore and adapt current Bayesian methods for joint longitudinal and survival modelling to accommodate the complexities of EHR-derived longitudinal data.

·      Develop Innovative Bayesian Models:

Create Bayesian models that seamlessly integrate bivariate longitudinal trajectories derived from EHR data and survival outcomes, capturing their joint dependencies and complexities.

·      Explore Efficient Computational Algorithms:

Develop efficient computational algorithms for Bayesian inference in joint models tailored to EHR data, ensuring scalability and computational feasibility.

·      Evaluate Methodologies:

Conduct extensive simulation studies and real-world applications using EHR data to assess the performance and generalizability of the proposed models.

·      Provide Practical Resources:

Offer comprehensive software implementations, practical guidelines, and educational resources to facilitate the adoption and utilization of Bayesian joint modelling techniques for analysing EHR-derived bivariate longitudinal trajectories and survival outcomes by healthcare researchers and practitioners.

What We Offer

·      A platform to work on pioneering research with tangible industrial applications.

·      Access to cutting-edge facilities and resources.

·      A nurturing and collaborative research community.

·      Expert guidance and mentorship from leaders in the field.

·      Embark on a transformative journey with us, where your passion for statistics machine learning, and big data analysis can contribute to the future of Health Care research. We look forward to welcoming an innovative and dedicated researcher to our team.

Candidate Profile

We are seeking a candidate who:

·      Has a profound interest in the intersection of statistics, machine learning, and big data analysis

·      Is eager to contribute to groundbreaking research in health care research.

·      Possesses a strong foundation in mathematics, statistics, or a related field.

·      Is experienced or keen to learn advanced machine learning techniques.

·      Is motivated to collaborate in a dynamic and innovative research environment.

For informal enquiries about the project, contact Dr Atanu Bhattacharjee, abhattacharjee001@dundee.ac.uk

For general enquiries about the University of Dundee, contact doctoralacademy@dundee.ac.uk

Our research community thrives on the diversity of students and staff which helps to make the University of Dundee a UK university of choice for postgraduate research. We welcome applications from all talented individuals and are committed to widening access to those who have the ability and potential to benefit from higher education.

QUALIFICATIONS

Applicants must have obtained, or expect to obtain, a UK honours degree at 2.1 or above (or equivalent for non-UK qualifications), and/or a Masters degree in a relevant discipline. For international qualifications, please see equivalent entry requirements here: www.dundee.ac.uk/study/international/country/.

English language requirement: IELTS (Academic) overall score must be at least 6.5 (with not less than 5.5 in reading, listening, speaking and 6.0 in writing). The University of Dundee accepts a variety of equivalent qualifications and alternative ways to demonstrate language proficiency; please see full details of the University’s English language requirements here: www.dundee.ac.uk/guides/english-language-requirements.

APPLICATION PROCESS

Step 1: Email Dr Atanu Bhattacharjee, abhattacharjee001@dundee.ac.uk to (1) send a copy of your CV and (2) discuss your potential application and any practicalities (e.g. suitable start date).

Step 2: After discussion with Dr Bhattacharjee, formal applications can be made via our direct application system. When applying, please follow the instructions below:

Candidates must apply for the Doctor of Philosophy (PhD) degree in Medicine (4 year) using our direct application system: apply for a PhD in Medicine.

Please select the study mode (full-time/part-time) and start date agreed with the lead supervisor.

In the Research Proposal section, please:

–         Enter the lead supervisor’s name in the ‘proposed supervisor’ box

–         Enter the project title listed at the top of this page in the ‘proposed project title’ box

In the ‘personal statement’ section, please outline your suitability for the project selected.