Research Fellow in Natural Language Processing Ref 6890
School/department: School of Engineering and Informatics
Hours:part time hours considered up to a maximum of 0.5 FTE. Requests for flexible working options will be considered (subject to business need).
Contract: fixed term until 31 August 2023
Salary: starting at £34,304 to £40,927 per annum, pro rata
Placed on: 21 September 2021
Closing date: 14 October 2021. Applications must be received by midnight of the closing date.
Expected interview date: To be confirmed
Expected start date: As soon as possible
The Artificial Intelligence group at the University of Sussex is looking for a Research Fellow to work on a large, interdisciplinary EU-funded project. This is a research- intensive role with high publication potential in the rapidly developing field of humane and ethical Articificial Intelligence. The aim of the HumanE AI Net project is to facilitate AI systems that enhance human capabilities and empower individuals and society as a whole while respecting human autonomy and self-determination, developing robust, trustworth AI systems capable of what could be described as “understanding” humans whilst adhering to European ethical values. Within the project component at the University of Sussex, the main research area that will be addressed is the use of natural language in human-in-the-loop machine learning, allowing humans to not just understand and follow the learning, reasoning, and planning process of AI systems (being explainable and accountable), but also to seamless interact with it, guide it, and enrich it with uniquely human capabilities, knowledge about the world, and the specific user’s personal perspective.
The main mechanism for implementing the research agenda of HumanE AI Net are collaborative microprojects. Your role will be to participate in regular consortium meetings for the different work packages, identify synergies with consortium partners and co-develop one or more microproject proposal. Subsequently, you will carry out the microproject over a period of 3-6 months together with researchers from the consortium partners, either at Sussex or at one of the partner universities. For example, at this stage of the project, your role might be to research, implement and evaluate various knowledge representations (including logic, neural networks, logic tensor networks and latent representations of knowledge such as embeddings) as well as methods for leveraging the afore-mentioned representations not just to present humans with explanations based on simple links between input and output space, but to be able reason about shared internal representations just like humans can intuitively explain to others how they arrive at certain conclusions.
Key Requirements. Candidates should have a PhD in computer science or an equivalent field, combined with a strong background in natural language processing and machine learning. The candidates should have demonstrable experience in python programming and relevant libraries e.g., pytorch, tensorflow and huggingface.
Please contact Dr Julie Weeds email@example.com for informal enquiries.
The University is committed to equality and valuing diversity, and applications are particularly welcomed from women and black and minority ethnic candidates, who are under-represented in academic posts in Science, Technology, Engineering, Medicine and Mathematics (STEMM) at Sussex.
You can find out more about our values and our EDI Strategy, Inclusive Sussex, on our webpages.
This role has been assigned an eligible SOC code and meets the salary requirements for Skilled Worker Sponsorship. Please consult our Skilled Worker Visa information page for further information about Visa Sponsorship.
Please note that this position may be subject to ATAS clearance if you require visa sponsorship.
How to apply
Download our academic application form [DOC 199.50KB] and Personal details and equal opportunities form [DOC 119.50KB] and fill in all sections.
Email your completed application, and personal details and equal opportunities form, to firstname.lastname@example.org
You should attach your application form and all documents to the email in PDF format (we are unable to accept applications as google.docs or .pages) and use the format job reference number / job title / your name in the subject line.
You can also send your application by post to Human Resources Division, Sussex House, University of Sussex, Falmer, Brighton, BN1 9RH.
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