Lecturer or Reader in Hybrid Artificial Intelligence

University of Edinburgh
March 02, 2023
Contact:N/A
Offerd Salary:£43,414 - £51,805
Location:N/A
Working address:N/A
Contract Type:Open-ended
Working Time:Full time
Working type:N/A
Ref info:N/A

Job Identification

6064

Job Category

Academic

Locations

  • Informatics Forum, Edinburgh, EH8 9AB, GB
  • Posting Date

    12/09/2022, 09:48 PM

    Apply Before

    02/03/2023, 12:00 AM

    Job Schedule

    Full time

    Health and Safety Requirements

    No key hazards identified for this post

    Criminal Record Check

    No criminal record check required

    Contract Type

    Open Ended

    Job Description

    Lecturer or Reader in Hybrid Artificial Intelligence

    Lecturer: UE08 £43,414 - £51,805 per annum

    Reader: UE09 £54,949- £61,823 per annum

    School of Informatics, Science and Engineering

    Full-time (35 hours per week), Open-ended

    Applications are invited for an academic position in Hybrid Artificial Intelligence in the School of Informatics at the University of Edinburgh. This post is part of a continuing drive to expand our research on the combination of symbolic reasoning and machine learning.

    The Opportunity:

    The successful candidates will hold (or be near to completing) a PhD, have an established research agenda, and display the enthusiasm and ability to undertake original research and to lead a research group. They will show excellent teaching capability and engagement with academic supervision. We are looking for current and future leaders in the field.

    In particular, we seek candidates with research interests in the development of hybrid AI methods that combine symbolic reasoning and neural learning , whereby neural networks can be used to model problems using data while considering domain knowledge encoded via symbolic techniques. Such an interplay can be used, for instance, to inject symbolic knowledge/constraints into neural network training or formally prove properties that the output of a neural network should obey.

    Candidates will need demonstrable experience in the development of principled approaches combining symbolic reasoning and neural-based learning and their applications to real-world domains e.g., healthcare. We are especially keen to address problems related to integrated and trustworthy AI, one of the School of Informatics' strategic priorities.

    The University of Edinburgh is one of the five founding partners of the UK's Alan Turing Institute for Data Science and Artificial Intelligence. This provides opportunities to interact with PhD students, research fellows and senior researchers. In addition, the School of Informatics is a member of the Confederation of Laboratories for Artificial Intelligence in Europe (CLAIRE). There are also ample opportunities within the University to pursue and drive collaborative activities with researchers in other areas of computer science, mathematics, and across the physical, social and biomedical sciences.

    For this post, areas of interest include (but are not limited to):

  • Theoretical foundations of hybrid/neurosymbolic AI;
  • Integration of structured domain knowledge into and querying of neural learning via symbolic/logic representation and reasoning;
  • Formal verification applied to neural networks and deep learning;
  • Applications of hybrid/neurosymbolic AI to complex domains such as safe robotics, medicine, health and care.
  • Candidates should have a strong technical track record and be interested and able to teach undergraduate and master's level courses in areas such as neurosymbolic AI and machine learning.

    Applicants must provide a recent CV, a research statement, and a teaching statement, which should specify the candidate's experience and approach to teaching, and what specialty and introductory (particularly undergraduate Informatics) courses they would be qualified to teach.

    We recognise that the pandemic may have affected some applicants disproportionately and aim to take this into account in the selection process. Applicants can optionally include a short statement regarding how their work has been disrupted by Covid, and how this affects their recent track record. This statement should be part of the cover letter and should not exceed one paragraph in length.

    Your skills and attributes for success:

    UE08 Lecturer:

  • PhD or equivalent (such as extensive industry experience), and experience as an established academic in Machine Learning or a related field
  • Candidates who are close to completing their PhD (ie. thesis submission is imminent), and who otherwise meet the selection criteria, will be considered.

  • Ability to undertake original research, including leading a research group.
  • Ability to attract research funding as an independent researcher.
  • A track record of first author and/or collaborative publications in high quality journals and international conferences.
  • Strong relevant research and teaching skills.
  • Effective written and oral communication skills in a range of contexts (e.g. teaching, research presentations and publications).
  • Ability to contribute to teaching on a range of non-Honours courses as well as in more specialist areas of machine learning.
  • The ability to engage with a range of teaching mediums including online and distance learning.

    Click here for a copy of the full job description for position of Lecturer

    UE09 Reader: as above and including:

  • Proven ability to provide leadership for activities in delivering the School's objectives.
  • Extensive experience in research, postgraduate supervision and teaching.
  • Proven ability to foster and embed a strong student-focused culture.
  • Evidence of significant achievement in the relevant field through (e.g.) successful knowledge transfer from research to academic community, public, private and/or voluntary sectors and general public; the receipt of prestigious prizes and awards; membership of national and international bodies relevant to the research field.
  • Experience of managing, motivating and developing research staff, students and projects
  • .PhD must be completed for a Reader appointment.

    Click here for a copy of the full job description for position of Reader

    Shortlisting for this post will take place in mid-February 2023 with interviews scheduled to be held 15th and 16th March 2023. Unfortunately, due to the level of applications feedback is only provided to interviewed candidates.

    Enquiries may be addressed to Prof Jacques Fleuriot ([email protected]).

    As a valued member of our team you can expect:

    An exciting, positive, creative, challenging and rewarding place to work. We give you support, nurture your talent and reward success. You will benefit from a competitive reward package and a wide range of staff benefits, which includes a generous holiday entitlement, a defined benefits pension scheme , staff discounts, family friendly initiatives , flexible working and much more. Access our staff benefits page for further information and use our reward calculator to find out the total value of pay and benefits provided.

    The University of Edinburgh holds a Silver Athena SWAN award in recognition of our commitment to advance gender equality in higher education. We are members of the Race Equality Charter and we are also Stonewall Scotland Diversity Champions, actively promoting LGBT equality.

    If invited for interview you will be required to evidence your right to work in the UK. Further information is available on our right to work webpages.

    The University is able to sponsor the employment of international workers in this role. If successful, an international applicant requiring sponsorship to work in the UK will need to satisfy the UK Home Office's English Language requirements and apply for and secure a Skilled Worker Visa.

    About Us

    As a world-leading research-intensive University, we are here to address tomorrow's greatest challenges. Between now and 2030 we will do that with a values-led approach to teaching, research and innovation, and through the strength of our relationships, both locally and globally.

    About the Team

    Informatics is the study of how natural and artificial systems store, process and communicate information. Research in Informatics promises to take information technology to a new level, and to place information at the heart of 21st century science, technology and society. The School enjoys collaborations across many disciplines in the University, spanning all three College, and also participates as a strategic partner in the Alan Turing Institute and, with Heriot-Watt University, in the Edinburgh Centre for Robotics.

    The School provides a fertile environment for a wide range of studies focused on understanding computation in both artificial and natural systems. It attracts students around the world to study in our undergraduate and postgraduate programmes, and currently has approximately 1000 undergraduate students, 320 MSc students and 350 PhD students. Informatics is one of seven schools in the College of Science and Engineering, at the University of Edinburgh. It is recognised for the employability of its graduates (demand exceeds supply), its contributions to entrepreneurship, and the excellence of its research. Since the first Research Assessment Exercise in 1986, Informatics at Edinburgh has consistently been assessed to have more internationally excellent and world-class research than any other submission in Computer Science and Informatics. The latest REF 2014 results have again confirmed that ours is the largest concentration of internationally excellent research in the UK. This contributes to our ranking in the top 15 CS departments world-wide according to the latest Times Higher Education ranking.

    We aim to ensure that our culture and systems support flexible and family- friendly working and recognise and value diversity across all our staff and students. The School has an active programme offering support and professional development for all staff; providing mentoring, training, and networking opportunities.

    The School of Informatics holds a Silver Athena SWAN award, in recognition of our commitment to advance gender equality in higher education and research.

    https:// www. ed.ac.uk/schools-departments/informatics

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