The Alan Turing Institute is the UK’s national institute for data science and artificial intelligence. The Institute is named in honour of the scientist Alan Turing and its mission is to make great leaps in data science and artificial intelligence research in order to change the world for the better.

The 'Finance and Economics' programme brings together leading experts in data science, machine learning, finance and the social sciences, from both academia and industry to tackle the most challenging questions by producing world-leading research with significant impact.

The programme works closely with government and the industry to exploit the potential of new technologies in the financial sector and economic research, and to position the UK as the leader in these areas. The programme is led by the Programme Director, Lukasz Szpruch.

The programme has recently received a significant investment from the Engineering and Physical Sciences Research Council (EPSRC) to deliver one of eight business-led “Prosperity Partnerships”.

This will see the Turing, HSBC, and other organisations in the financial sector developing a Framework for responsible adoption of Artificial Intelligence in the financial services industry (FAIR).

FAIR brings together academia and industry to advance research and develop practical and scalable solutions needed to fully realise the transformational benefits of responsible adoption of AI across the financial services industry.

FAIR has five main research themes:

1. Robustness and Resilience

2. Privacy and Security

3. Fairness and Transparency

4. Verification and Accountability

5. Integration Environment

Find out more: FAIR: Framework for responsible adoption of artificial intelligence in the financial services industry.

We are hiring a team of Research Associates to support and enable the delivery of the five main research themes under the direction of the Turing Programme Director, and the project PIs. The team will collectively have a broad range of expertise, and we will be hiring based on varied skills required for each specific challenge.

We are looking for two Research Associates to support and enable the delivery of this project under the direction of Professor Carsten Maple.

ROLE PURPOSE

The successful candidate will work in partnership with our industry partner HSBC on a project that is aligned to the Privacy and Security research theme within FAIR. This project will investigate the use of Federated Learning and Federated Analytics across different jurisdictions to improve data models.

Privacy-enhancing technologies such as differential privacy are sometimes used to overcome privacy concerns linked to Federated Learning, and this project will explore the impact on efficacy when using privacy techniques in federated environments.

The project will also explore the role of other techniques such as Multi-Party Computation and Homomorphic Encryption as a means of information sharing and will consider use cases such as fraud prevention.

Deliverables for this project include analysis of the state-of-the-art in federated learning, federated analytics and trustworthy information sharing and analysis of the data to clarify the advantages and disadvantages associated with each approach.

The candidate will join a vibrant team of researchers working in Privacy and Security and will have opportunities to engage with cutting-edge projects and experts at leading universities.

These will include Sam Cohen, Gesine Reinert and Marta Kwiatkowska (Oxford), Carsten Maple and Graham Cormode (Warwick), Adrian Weller (Cambridge), Philip Treleaven (UCL) and Lukasz Szpruch (Edinburgh), as well as project teams funded by other strategic partnerships.

DUTIES AND AREAS OF RESPONSIBILITY

• Apply state-of-the-art and novel techniques for secure and private data sharing emerging from the Institute and elsewhere to the business-inspired research challenges of the Turing partnerships:
• Develop methods for creating a shared learning from distributed data which is not shared itself.
• Develop data-science tools and pipelines to an industrial standard.
• Develop metrics for evaluating the efficacy and privacy of data sharing across multiple use cases.
• Provide methodologies for assessing the efficacy and privacy trade-offs.
• Enable data sharing between organisations and different departments within an organisation.
• Scope, pilot and deliver high-quality research activity in partnership with partner stakeholders, and under the direction of the Principal Investigator and Programme Director:

Other duties:

• · Present, disseminate and explain our work at internal and external events hosted by Turing and/or the partner.

Essential:

• Research Associate level: PhD in Mathematics, Computer Science or a closely related discipline.
• Research Assistant level: Near completion of a PhD or equivalent level of professional qualification in Mathematics, Computer Science, or closely related discipline.
• A solid background in one or more of the following: Differential Privacy, Federated Learning, Federated Analytics, Secure Multiparty Computation, or Homomorphic Encryption.
• Experience in design, development, and implementation of research software libraries, ideally using one of the following: Python, R, Julia, and their associated frameworks.
• Track record of the ability to initiate, develop and deliver high-quality research aligned with the research strategy indicated by the PI and any industrial stakeholders and to publish in peer-reviewed journals and conferences.
• Hands-on experience with Machine Learning methods.
• Track record of outstanding research and in delivering impact appropriate to career stage.
• Experience in publishing research papers, code libraries or technical reports and giving presentations or classes on technical subjects.

If you are interested in this opportunity, please click the apply button below. You will need to register on the applicant portal and complete the application form including your CV and covering letter. If you have questions about the role or would like to apply using a different format, please contact us on 020 3970 2148 or 0203 862 3340, or email [email protected].

If you are applying for more than one role at the Turing, please note that only one Cover Letter can be visible on your profile at one time. If you wish to apply for multiple roles and do not want to overwrite your existing Cover Letter, please apply for the role using the button below and forward your additional cover letter directly to [email protected] quoting the job title.

TERMS AND CONDITIONS

This full-time post is offered on a 2-year fixed-term basis. The annual salary is £37,000-£42,000 (depending on experience) plus excellent benefits, including flexible working and family friendly policies, https://www.turing.ac.uk/work-turing/why-work-turing/employee-benefits

Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant at a salary of £34,500 per annum.

Successful candidates will be employed by the Alan Turing Institute, but to access data for the project they may also need to be onboarded as a Category B supplier for HSBC.

CLOSING DATE FOR APPLICATIONS: 03 January 2022 at 23:59

EQUALITY, DIVERSITY AND INCLUSION

The Alan Turing Institute is committed to creating an environment where diversity is valued and everyone is treated fairly. In accordance with the Equality Act, we welcome applications from anyone who meets the specific criteria of the post regardless of age, disability, ethnicity, gender reassignment, marital or civil partnership status, pregnancy and maternity, religion or belief, sex and sexual orientation.

We are committed to building a diverse community and would like our leadership teal to reflect this. We therefore welcome applications from the broadest spectrum of backgrounds.

Reasonable adjustments to the interview process will be made for any candidates with a disability.

Please note all offers of employment are subject to continuous eligibility to work in the UK and satisfactory pre-employment security screening which includes a DBS Check.

Full details on the pre-employment screening process can be requested from [email protected].