Job offer

Research Field Computer science

Education Level Bachelor Degree or equivalent, Applicants will be educated to at least first degree level (or equivalent qualification/experience) in a relevant discipline (e.g., Computer Science, Communication Engineering, Electrical/Power Engineering, Energy Systems, Applied Mathematics, Data Science, Cybersecurity, Artificial Intelligence) and be able to demonstrate sufficient knowledge of research methods and techniques to work within established research programmes.

The successful applicant will be able to present research progress and outcomes, communicate complex information (orally, in writing and electronically), and contribute to proposals and applications to external bodies. Specific Requirements

Applicants will be able to:

• Demonstrate strong quantitative and analytical skills and an ability to learn new methods quickly.
• Show interest in Computer Science/Internet-of-Energy/Cybersecurity/Artificial Intelligence and their data, modelling, and operational challenges.
• Develop and evaluate algorithmic solutions (e.g., machine learning, optimisation, statistical modelling, distributed systems), depending on project direction.
• Implement research prototypes and run reproducible experiments using programming and tooling.
• Work with datasets, including data preparation, experimental design, benchmarking, and reporting of results.
• Collaborate effectively with supervisors and partners, including contributing to network-wide training, secondments, and dissemination.

Please ensure you read the Job Description and Person Specification at the link, for full details of this role.

Languages ENGLISH, Computer science, * Applicants will possess an undergraduate degree (2:1 or above) or equivalent in a relevant scientific field and excellent communication skills.

• Full MSCA-aligned employment contract with competitive salary for three years.
• Starting salary will be 33,951 GBP
• An additional supplementary allowance of ~£3300* per annum which attracts both NI and pension.
• Mobility allowance (~£5750*/year), and family allowance if applicable (~£4000*/year) adjusted for the cost of living in the host country (in this case UK).
• *Values subject to exchange rate when appointment is made.
• Access to state-of-the-art facilities, laboratories and expert supervision.
• International secondments and training events and networking with 11 fellow PhD students from the SAILING MSCA Doctoral Network., * All researchers recruited must be doctoral candidates (i.e. not already in possession of a doctoral degree at the date of the recruitment) and must undertake transnational mobility. Researchers who have successfully defended their doctoral theses, but who have not yet formally been awarded the doctoral degree will not be considered eligible.
• Under the rules of the scheme European and International applications are welcomed, subject to the UKVI regulations on the Right to Work in the UK.
• Applicants must comply with the MSCA DN mobility rule: Researchers must not have resided or carried out their main activity (work, studies, etc.) in the country of the recruiting beneficiary for more than 12 months in the 36 months immediately before their date of recruitment. Compulsory national service, short stays such as holidays, and time spent as part of a procedure for obtaining refugee status under the Geneva Convention are not taken into account.

Selection process

• We follow an open, transparent, merit-based, impartial and equitable recruitment process in line with the European Charter for Researchers and the Code of Conduct for the Recruitment of Researchers .
• Whilst all applicants will be judged on merit alone, we particularly welcome applications from groups currently underrepresented within our working community. The University of Exeter is dedicated to promoting the role of women in science, and, therefore, explicitly invites women to apply.

The SAILING Doctoral Network (DN) aims to train 12 next generation scientists in creating an intelligent and automated energy management system powered by secure AI and digital twin for the Internet-of-Energy (IoE). For this role [DC4: Blockchain-secured data sharing in IoE] the successful candidate will undertake a PhD project focusing on developing blockchain-enabled secure data sharing techniques for IoE to minimize malicious data tampering and destruction. The key objectives are to develop a holistic design of the blockchain architecture for IoE, a scalable blockchain system for IoE data sharing, and an efficient and fair consensus mechanism for IoE. The SAILING DN will carry out the project on an international and inter-sector scale via extensive collaboration and knowledge sharing. Individual projects within the SAILING programme map into five interrelated science objectives: 1) to create a high-fidelity IoE digital twin; 2) to develop secure AI techniques for IoE; 3) to design an intelligent and scalable IoE energy management strategy; 4) to develop agile IoE fault detection and accurate failure prediction methods; 5) to construct an intelligent energy optimisation system. SAILING combines excellent training for doctoral researchers, diverse supervisions and international mobility for impactful research to benefit society and the economy, providing its Doctoral Candidates (DCs) with skills and knowledge "most sought-after" in academic and non-academic employability sectors.