Research Associate in the Cambridge Image Analysis group (Fixed Term)

Updated: 13 days ago
Location: Cambridge, ENGLAND
Job Type: Permanent
Deadline: 20 Nov 2020

We invite applications for a Post-Doctoral Research Associate to work in the Cambridge Image Analysis group at the Department of Applied Mathematics and Theoretical Physics, University of Cambridge.

The Cambridge Image Analysis Group (CIA) specialises in the mathematics of inverse problems in imaging, digital image and video processing using partial differential equations, variational methods and machine learning. Our research ranges from the modelling and analysis of such methods to their computational realisation and application.

The research activity of the successful candidate will take place within the CIA, and more specifically, within a multidisciplinary project on inverse problems related to cryo-EM. This project is a collaboration between the CIA, the group of Sjors Scheres at the Laboratory for Molecular Biology (Cambridge), Ozan Öktem (KTH and Edinburgh) and the Alan Turing Institute. The particular focus of the project is the design of hybrid mathematical and machine learning methods for cryo-EM image and atomistic model reconstruction. This is an exceptional opportunity to conduct ambitious research whilst collaborating with an interdisciplinary team.

Duties include developing and conducting individual and collaborative research objectives, proposals and projects. The role holder will be expected to plan and manage their own research and administration, with guidance if required, and to assist in the preparation of proposals and applications to external bodies. You must be able to communicate material of a technical nature and be able to build internal and external contacts. You may be asked to assist in the supervision of student projects, the development of student research skills, provide instruction and plan/deliver seminars relating to the research area.

Applicants must have (or be about to receive) a PhD degree in mathematics or statistics (or a closely related discipline). The ideal candidate will be experienced in one or more of the following areas: inverse problems, mathematical imaging, machine learning, cryo-EM, computational analysis, optimisation and/or data science. Experience in parallel computing and python/C programming skills are desirable.

Informal inquiries can be made by contacting LE24307@maths.cam.ac.uk

Start date: 1 January 2021

Please indicate the contact details of two academic referees on the online application form and upload a full curriculum vitae and a one-page summary of research achievements and interests in relation to the above projects. Please ensure that at both of your referees is contactable at any time during the selection process, and is made aware that they will be contacted by the Mathematics HR Office Administrator to request that they upload a reference for you to our Web Recruitment System; and please encourage them to do so promptly.

Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.

You will need to upload a full curriculum vitae, list of publications, research statement (up to 3 pages), and the contact details of at least two academic referees. Please ensure that your referees supply references by the closing date and are made aware that they may be contacted by the Mathematics HR Office Administrator to request that they upload a reference for you to our Web Recruitment System; and please encourage them to do so promptly.

Please quote reference LE24307 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. We particularly welcome applications from women and /or candidates from a BME background for this vacancy as they are currently under-represented at this level in our Department.

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

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