Eine vollständige Bewerbung in einer Minute
Maßgeschneiderter Lebenslauf und Anschreiben – versandbereit.
The University of Manchester invites applications for a Research Associate in statistics, biostatistics, data science, computer science, applied mathematics, or related quantitative discipline. You will contribute to the UKRI Future Leaders Fellowship on reirradiation, working in a multidisciplinary team within the Radiotherapy Related Research group at the Paterson Building, Withington.
The role requires strong statistical modelling, causal inference, and programming skills in Python/R, with
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.
We welcome candidates who bring diverse perspectives, experiences, and approaches to their work.
We encourage applications from individuals with a wide range of backgrounds and experiences. You should demonstrate:
We value transferable skills and real-world experience as much as formal qualifications.
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.
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.