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Research Associate in Formalising Neuro-Symbolic AI

The University of Manchester - Science and Engineering - Department of Computer Science - School of Engineering

Location: Sheffield
Salary: £36,924 to £39,105
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 31st October 2024
Closes: 6th January 2025
Job Ref: SAE-027105

Job reference: SAE-027105
Salary: £36,924-£39,105 per annum, dependent on relevant experience
Faculty/Organisational Unit: Science and Engineering
Location: Oxford Road
Employment type: Fixed Term
Division/Team: Department of Computer Science
Hours Per Week: Full Time (1 FTE)
Closing date (DD/MM/YYYY): 06/01/2025
Contract Duration: 24 months
School/Directorate: School of Engineering

Autonomy and Verification Group - Department of Computer Science

This position is to carry out research within the Autonomy and Verification Group on formalising and analysing Neuro-Symbolic AI. Although Neural AI approaches (machine learning, neural networks, etc) can be fast and flexible, they tend to be opaque and prone to uncertainty and although Symbolic AI approaches (rule-based systems, logic) can provide explainability and verifiability they tend to be slow and inflexible. An obvious route is to use a combination of the two, in the form of Neuro-Symbolic AI.

We are looking for a strong researcher able to conduct research on logic and formal methods, with a particular focus on providing a formal basis for Neuro-Symbolic AI. This will require expertise in Temporal Logic, formalising Hybrid Systems, Category Theory, or formal aspects of Neuro-Symbolic AI.

This work fits together with our research on formal methods, on autonomous systems (such as robotics and AI), and on verification and validation. The successful candidate will also undertake this research as part of the wider Autonomy and Verification Network.

Department of Computer Science: www.cs.manchester.ac.uk/research

Manchester Centre for Robotics and AI: www.robotics.manchester.ac.uk

Autonomy and Verification network: autonomy-and-verification.github.io

What you will get in return

  • Fantastic market leading Pension scheme
  • Excellent employee health and wellbeing services including an Employee Assistance Programme
  • Exceptional starting annual leave entitlement, plus bank holidays
  • Additional paid closure over the Christmas period
  • Local and national discounts at a range of major retailers

As an equal opportunities employer we welcome applicants from all sections of the community regardless of age, sex, gender (or gender identity), ethnicity, disability, sexual orientation and transgender status.  All appointments are made on merit.

Our University is positive about flexible working – you can find out more here

Hybrid working arrangements may be considered.         

Please note that we are unable to respond to enquiries, accept CVs or applications from Recruitment Agencies.

Any recruitment enquiries from recruitment agencies should be directed to People.Recruitment@manchester.ac.uk.

Any CVs submitted by a recruitment agency will be considered a gift.

Enquiries about the vacancy, shortlisting and interviews:

Name: Prof. Michael Fisher 

Email: michael.fisher@manchester.ac.uk

General enquiries:

Email: People.recruitment@manchester.ac.uk

Technical support: jobseekersupport.jobtrain.co.uk/support/home

This vacancy will close for applications at midnight on the closing date.

 

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