Research Associate in Spatiotemporal Causal Inference:Paterson Building

Job Description

This is an outstanding opportunity for a Research Associate, with a background in statistics, biostatistics, data science, computer science, applied mathematics, or a related quantitative discipline, to work within the reirradiation research team under the supervision of Dr Vasquez Osorio. The post holder will be part of the Radiotherapy Related Research (RRR) group, which is based at the Paterson Building in Withington.

The candidate will support the aims of Dr Vasquez Osorio’s UKRI Future Leaders Fellowship on Advancing Reirradiation and Treatment Outcome Understanding with Robust Dose Mapping and Causal Inference. This innovative project will study how advanced spatiotemporal causal inference methods can be developed and applied to complex radiotherapy datasets to understand the relationship between radiation dose and treatment outcomes, enabling improved evidence-based decision-making for patients undergoing reirradiation.

This position offers an ideal opportunity for an enthusiastic, well-motivated individual to work as part of a sociable multidisciplinary team consisting of physicists, computer scientists, clinicians, radiographers, and imaging experts. The ideal candidate will have excellent interpersonal, communication, programming, and organisational skills, and will be able to work with minimal supervision. Experience of advanced statistical modelling, causal inference methods, and programming for the analysis of complex datasets is essential for the position.

You will be responsible for

• developing research objectives and proposals for own or joint research, with the assistance of a mentor if required.
• conducting individual and collaborative research projects.
• writing up research work for publication.
• communicating complex information, orally, in writing and electronically.
• using creativity to analyse and interpret research data and draw conclusions on the outcomes.

We welcome candidates who bring diverse perspectives, experiences, and approaches to their work.

About

You

We encourage applications from individuals with a wide range of backgrounds and experiences. You should demonstrate:

Essential Criteria

• having, or being about to obtain, a relevant PhD (or equivalent).
• experience in advanced statistical modelling and/or causal inference methods.
• ability to develop or adapt novel computational or statistical methods (beyond application of existing techniques).
• strong programming skills (e.g. Python and/or R).
• knowledge of radiotherapy, cancer research, medical imaging, or clinical data analysis.

Desirable Criteria

• experience analysing complex biomedical, healthcare, or spatiotemporal datasets.
• experience with spatiotemporal methods.
• track record of presenting at national and international conferences.

We value transferable skills and real-world experience as much as formal qualifications.

Our benefits include

• Generous employer contribution pension
• 29 days annual leave plus bank holidays, along with Christmas closure
• Ride to work and EV car scheme available

For more information, please see University of Manchester Benefits . You can also find information on our Flexible and Hybrid working here .

We are an open place of enquiry and challenge. We embrace and celebrate difference, diversity and debate, and we pride ourselves on being a place of education, learning and community where we are able, within the law, to question and test received wisdom, express new ideas and explore controversial or unpopular topics and opinions. Find out more from our Freedom of Speech Policy .

Enquiries about the role, shortlisting and interviews

Name: Dr Eliana Vasquez Osorio / Dr Ruth Forman

Email Address: Eliana.vasquezosorio@manchester.ac.uk / ruth.forman@manchester.ac.uk

General enquiries and administrative support

recruitmentservices.people@manchester.ac.uk

Technical and job portal support

https://jobseekersupport.jobtrain.co.uk/support/home

Applications close at midnight on the closing date.

Further particulars (with person specification) linked below.