The School of Physical Sciences invites applications for two University Assistant/Associate Professorships in the field of Data Intensive Science to be held either in, or shared between, the Department of Physics, the Department of Applied Mathematics and Theoretical Physics, and the Institute of Astronomy.

The Departments and School are looking for talented career scientists to develop and promote an ambitious research programme aimed at understanding fundamental mechanisms in their subject area through advanced analysis of large scientific datasets. The research area of the lectureship in Physics, Astronomy, Mathematics or associated areas is broadly defined and depending on this the position will be based in either the Department of Physics, the Department of Applied Mathematics and Theoretical Physics, the Institute of Astronomy, or held jointly between two departments.

The successful candidates will have a world-class research record. We are particularly interested in applicants applying advanced data analysis techniques to large experimental or observational data sets to answer fundamental research questions which should strengthen the long-term research directions in data intensive science in the host departments. Potential research topics for the role are broadly defined to include any area compatible with the research programmes in the host departments. However, some emphasis will be given to the following fields: Gravitational Wave Astronomy, Radio Astronomy, High Energy Physics, Stellar Dynamics and Accretion Disks, Cosmology, Data-driven discovery in complex matter and biophysics, or Imaging Analysis.

The successful candidates would be expected to play a leading role in expanding interdisciplinary research activities in Data Intensive Science and would play a significant role in reinforcing the links between data intensive research groups in the Departments within the School of the Physical Sciences, and across the wider University.

In addition to the strong research focus of the position, the successful candidates would be expected to play a leading role in the new MPhil programme in Data Intensive Science that will see its first cohort arrive in 2023. The MPhil is a cross-Departmental Programme in the School of Physical Sciences which aims to provide education of the highest quality at Master's degree level covering the full range of skills required for scientific data analysis. It is expected that the successful candidates would initially be responsible for leading the delivery of teaching related to statistical analysis and/or machine learning as part of the programme. The candidates would also support the other aspects of the MPhil programme to ensure its successful delivery.

Applicants should have a PhD in mathematics, astrophysics, or physics (or a cognate discipline), a strong record of relevant research in Data Intensive Science and must show evidence of enthusiasm and ability to teach a wide range of courses successfully at both undergraduate and master's degree level. This work will include the delivery of existing courses and the development of new MPhil lecture courses, teaching materials, examinations, data science projects, and demonstration classes.

The Departments are active in promoting policies to address historic under-representation of women and minority groups in its workforce. Candidates from under-represented groups, as well as candidates with a track record in addressing barriers to equality and diversity in education, are particularly encouraged to apply.

Given the nature of these posts, the teaching load of the appointees will be directed initially toward the Masters' programme. General contribution to the academic work of the host Department(s) and the University beyond teaching and research, will be commensurate with the appointee's interests and skills, and the requirements of the host Department(s).

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.

For the complete job description and instructions about how to Apply please visit the official website: https://www.jobs.cam.ac.uk/job/36147/