Location: Trinity College Dublin
Level: Academic

Post Status: Tenure Track - This position is a Tenure Track position which is 5-years in the first instance, permanency is subject to satisfying the tenure requirements.
Department/Faculty: Discipline of Artificial Intelligence, School of Computer Science and Statistics, Faculty of STEM
Reports to: Head of School, Computer Science and Statistics
Salary: [€35,509 to €50,410 €86,247 per annum]
Full job description
APPLICATIONS WILL ONLY BE ACCEPTED BY E-RECRUITMENT: http://jobs.tcd.ie

If you have any application queries, please contact: recruit@tcd.ie

[Interviews for this position will take place on 23rd April 2021]

Post Summary

The School of Computer Science and Statistics is seeking to appoint an Assistant Professor in Computer Science (Artificial Intelligence). The successful candidate will be an outstanding researcher and teacher who has a strong international research track record and the potential to become a research leader. A strong commitment to teaching, research excellence, developing academic and industrial research partnerships, and the ability to establish a dynamic, high impact, world-class research programme are essential. Candidates in all human facing aspects of AI will be considered. Applications are encouraged from candidates working in areas including, but not limited to: recommender systems; information retrieval; natural language processing; forms of AI-driven digital engagement that are multi-modal, task- oriented, personalised, context-aware, explainable and trustworthy; and approaches to digital engagement employing deep neural networks or knowledge graphs. The post holder will join a vibrant School, top ranked in Ireland, and may be affiliated with the ADAPT Research Centre for Digital Content Technology which pioneers new forms of proactive, scalable and integrated AI-Driven Digital Content Technology that empower individuals and society to engage in digital experiences with control, inclusion and accountability.

The successful applicant must have a PhD in Computer Science or a related discipline. The School particularly welcomes applicants who will play an active role in interdisciplinary research within the School, E3 and the University. The E3 initiative is an ambitious project to expand education and research activities across three of its Schools: Computer Science and Statistics, Engineering, and Natural Sciences. The School will support the successful applicant with funding to recruit one PhD student. Furthermore, the postholder can seek further PhD funding under the SFI funded Centres for Research Training (CRTs) hosted in the School which all offer PhD positions in AI-related areas. The successful candidate may join the SFI funded ADAPT Research Centre for Digital Content Technology and benefit from its large and diverse streams of research funding. With its CRTs and SFI Research Centres, the School offers a supportive environment for researchers to advance their careers.

Further Information

Informal enquiries about this post should be made to dave.lewis@scss.tcd.ie Head of Discipline

Standard Duties and Responsibilities of the Post Research:

As part of research duties, the appointee is required to engage in research and/or other creative and innovative activity as appropriate to the Discipline. The appointee is required to disseminate their research in academic publications, recognised conferences, or other outlets as appropriate. The appointee is encouraged to engage in initiatives to seek funding for research in their own field and/or interdisciplinary or multidisciplinary research as appropriate. The appointee is also required to be available to participate in postgraduate research supervision including student recruitment, thesis definition, preparation, advice and regular advisory and guidance meetings.

Teaching:

As part of normal teaching duties, the appointee is obliged to give instruction and supervision, as directed by the Head of School (or designated Head of Discipline), to undergraduate and postgraduate students of the University in courses and programmes organised by the School. It is expected that the candidate will be responsible for delivering teaching in digital engagement, machine learning, natural language processing, information management and knowledge engineering as well as introductory topics in computer science.

Such duties include curriculum and course design, preparation and delivery of lectures, tutorials and general examination and other assessment duties. The appointee is also required to be available to students for academic guidance and advice. In some disciplines, academic activities may also include laboratory, workshop or clinical instruction, supervision of fieldwork, site visits and other off-campus activities.

Contribution and Scholarly Activity:

As part of the contribution to the School and University, the appointee is required to participate in academic administration at School level (as directed by the Head of School), and/or University level. In representing the University externally, the appointee is required to maintain the highest professional standards. The appointee is also required to commit to engage in scholarly activity such as,

but not limited to, refereeing of journals, external examining, membership of learned societies, advisory bodies and peer review panels.

Person Specification

Qualifications

Successful candidate must have a PhD in Computer Science or a related discipline.

Knowledge and Experience Research:

  • Proven record of excellence in artificial intelligence research demonstrated by a strong publication record in peer-reviewed conferences and journals.
  • Proven record and ability to contribute to the field of computer science in human-facing aspects of AI. Aspects of interest include, but are not limited to: recommender systems; information retrieval; natural language processing; forms of AI-driven digital engagement that are multi- modal, task-oriented, personalised, context-aware, explainable and trustworthy; and approaches to digital engagement employing deep neural networks or knowledge graphs.
  • Demonstrate research plans which complement the strategic plans of the School of Computer Science and Statistics, E3 and the ADAPT Centre.
  • Ability to attract external research funding.
  • Ability for research collaboration with industry and across disciplines.

Teaching

  • A demonstratable ability to provide high quality lectures and practical classes in computer science to undergraduate and postgraduate students.
  • Excellent communication and interpersonal skills.
  • A commitment to excellence in teaching.
  • Ability to supervise undergraduate projects and postgraduate dissertations.
  • Ability to recruit and supervise research postgraduate students.
  • Ability to develop new modules and teaching material.
  • An ongoing commitment to using new teaching media.
  • Ability to work collaboratively and effectively in an inter and multidisciplinary environment.

Contribution and Scholarly Activity:

  • Willingness to contribute to the Discipline, School, E3, SFI Research Centres, College and to the wider community.
  • The ability to participate in academic administration at School, and/or University levels.
  • Ability to co-ordinate, manage and develop modules and courses in the School.
  • Excellent organisational and administrative skills.
  • Ability to establish targets and goals to support School, College and Research Centre strategies.
  • A commitment to student care, advancing gender equality and equal opportunities.
  • Ability to organise research seminars, recruitment initiatives and other activities.

Skills & Competencies

  • Ability to maintain high professional standards
  • Ability to work effectively and efficiently
  • Ability to be flexible when necessary
  • A strong team player
  • Career driven, enthusiastic and motivated.
  • A commitment to own professional development