Assistant/Associate Professor in Data Intensive Science x 2

Submission Information
Publish Date: 
Thursday, August 11, 2022
Archive Date: 
Thursday, October 6, 2022
The upcoming date less then 1 day.
Job Summary
Job Category: 
Faculty Positions (tenure and tenure-track)
Institution Classification/Type: 
Foreign
Institution/Company: 
University of Cambridge
Department Name: 
Department of Physics, the Department of Applied Mathematics and Theoretical Physics, and the Institute of Astronomy
City: 
Cambridge
State/Province: 
Cambridgeshire
Country: 
United Kingdom of Great Britain and Northern Ireland
Announcement
Job Announcement Text: 

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. Salary is £42,149 - £53,348 or £56,587 - £60,002 per annum.

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).

Click the 'Apply to job' URL link Below to register an account with our recruitment system (if you have not already) and apply online.

To view further particulars about the job, please click on the 'Apply to job' URL.  You can view without applying.

Applicants should submit the following documents with their application:

  • Curriculum Vitae (CV)

  • A list up to ten publications. For large collaborative papers please detail your personal contribution.

  • A research proposal of no longer than 3 pages, highlighting synergies with existing research activities within the relevant departments and how they might enhance interdisciplinary interactions in data science.

  • A statement of up to two pages setting out your approach to teaching and the contributions you can make to the new MPhil programme in Data Intensive Science.

Details of three referees, including e-mail address and phone number, whom the University of Cambridge can contact for references should be listed in the web application form. Referees will be contacted via the web application system after the application closing date.

If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application.

Please quote reference KA32385 on your application and in any correspondence about this vacancy.

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.

Included Benefits: 

What the University of Cambridge has to offer

Application Deadline: 
Friday, September 30, 2022
Selection Deadline: 
Tuesday, January 31, 2023
Current Status of Position: 
Accepting Applicants
Apply to Job
Attention To: 
KA32385 Selection Committee
Institution/Company Job ID or Reference Code: 
KA32385
Inquiries About Job
Attention To: 
Dr James Fergusson
Subject: 
KA32385 Assistant/Associate Professor in Data Intensive Science
Email: 
J.Fergusson(at)damtp.cam.ac.uk