We are looking for a Research Associate to join an ambitious project in the space of Secure & Privacy-preserving AI Models.
You will enjoy designing, developing and evaluating novel AI models (deep neural networks) that are privacy-preserving and robust against attacks. The project will involve the continuous interaction with experts in explainable AI and formal software verification. You will also have the opportunity to build use cases and to collaborate with domain experts in areas such as cancer research and energy trading. You will design, develop and evaluate new models in the context of their accuracy, privacy-protection and robustness. This position may include research on a diverse set of techniques such as federated learning, homomorphic encryption, multiparty computation and adversarial methods. The post is initially for one year, with the possibility for extensions.
You should have a PhD or equivalent in Computer Science or a closely related field together with a track record of international publications in applied machine learning or secure computation. Examples of fields of interests are:
(1) Federated Learning
(2) Homomorphic Encryption
(3) Secure Multiparty Computation
(4) Differential Privacy
(5) Safety Mechanisms in AI Systems
(6) Adversarial Methods
As this role involves research at a postgraduate level, applicants who are not an EEA national or a national of an exempt country and who will require sponsorship under the Skilled Worker route of the UK Visas and Immigration’s (UKVI) Points Based System in order to take up the role, will be required to apply for an Academic Technology Approval Scheme (ATAS) Certificate and will need to obtain this prior to making any official visa application UKVI)
The School/Department is strongly committed to promoting equality and diversity, including the Athena SWAN charter for gender equality in higher education. The School/Department holds a Bronze Award for their good practice in relation to gender; including flexible working arrangements, family-friendly policies, and support to allow staff to achieve a god work-life balance. We positively welcome applications from women for this post. All appointments will always be made on merit. For further information, please visit:
Our University is positive about flexible working – you can find out more here
Blended working arrangements may be considered
Please note that we are unable to respond to enquiries, accept CVs or applications from Recruitment Agencies.
Enquiries about the vacancy, shortlisting and interviews:
Name: M. Mustafa
This vacancy will close for applications at midnight on the closing date.
Please see the link below for the Further Particulars document which contains the person specification criteria.