Research Associate

The International Society for Bayesian Analysis; Sheffield; On-site; GBP 37,099 - 45,585; Full time

Job summary

A leading research institution is seeking a Research Associate to support a project focusing on the development of Bayesian expert elicitation protocols. This role involves working closely with faculty to enhance the quality of archaeological dating methods through innovative software development.

Qualifications

• PhD in related field or actively pursuing one.
• Programming experience in R or Python preferred.
• Familiarity with expert elicitation and Bayesian methods desirable.

Responsibilities

• Develop Bayesian expert elicitation protocols and software.
• Work with faculty on archaeological dating evidence.
• Improve consistency and reuse of dating evidence.

Skills

Programming skills

Bayesian inference

Qualitative data analysis

Education

PhD in Statistics, Science-based Archaeology or related subject

Tools

R

Python

Job description

Job Title: Research Associate

Contract Type: Fixed-term with an initially fixed end date of 3rd December 2025.

Location: University of Sheffield, Sheffield, UK

Faculty: Faculty of Science

Department: School of Mathematics and Statistics

Salary: Grade 7, £37,099-£45,585 per annum

Closing Date: 12th February 2024

Role Summary:

Applications are invited for a Research Associate in the School of Mathematics and Statistics. You will be working with Prof Caitlin Buck and Professor Jeremy Oakley to develop Bayesian expert elicitation protocols and software, as part of research funded by the Leverhulme Trust project “Quantifying Uncertainty in Expert Archaeological Dating Evidence” (QUEADE).

You will develop new protocols and open-source software to allow experts in archaeological finds, such as coins and pottery, to formalise their knowledge about the dates of cultural objects that cannot readily be dated using scientific methods (such as radiocarbon dating). The goal will be to quantify the expert knowledge using formal probability statements, which has not been done before. By doing this, the QUEADE project will improve the consistency and reusability of dating evidence for the most commonly dated finds from archaeological sites and, in the process, add enormously to the quality and quantity of dating evidence available.

You should have (or be working towards) a PhD in Statistics, Science-based Archaeology or a related subject, and have confident programming skills, preferably with knowledge of R or Python. A background in at least one of expert elicitation, Bayesian inference, or qualitative data analysis is desirable, but not essential. We are happy to consider applicants who are working on one or more of these topics as part of a PhD and who would like to join QUEADE for 18 months, as a research internship during their studies.