Deep Learning Research Fellowship : Professor/Associate Professor/Senior Lecturer (Researcher) V000285

Listing reference: nwu_002023
Listing status: Closed
Apply by: 1 October 2023
Position summary
Industry: Education & Training
Job category: Others: Education and Training
Location: Potchefstroom
Contract: Fixed Term Contract
Remuneration: The annual total remuneration package will be commensurate with the level of appointment as advertised and in line with the NWU policy guidelines.
About our company
NWU
Introduction
NORTH-WEST UNIVERSITY (POTCHEFSTROOM CAMPUS) FACULTY OF ENGINEERING POSITION NUMBER: V000285 VACANCY: PROFESSOR/ASSOCIATE PROFESSOR/SENIOR LECTURER (RESEARCHER) PEROMNES: A5, A6, A7 EMPLOYMENT TYPE: 3 YEAR FIXED TERM APPOINTMENT
Job description

The MUST Deep Learning research group performs basic and applied research in machine learning, with an emphasis on the theory and application of deep learning. Our theoretical work studies the generalisation ability and interpretability of deep learning models from novel perspectives. Our application domains are diverse, currently ranging from environmental monitoring and space weather prediction, to industrial applications of deep learning.
 
MUST (www.nwu.ac.za/must) forms part of the Faculty of Engineering at North-West University (NWU), South Africa. It is a node of the South African National Centre for Artificial Intelligence Research (CAIR), and the coordinator of the machine learning research programme of The National Institute for Theoretical and Computational Sciences (NITheCS). As such, the group develops and applies specialised machine learning techniques with a network of collaborating researchers.
 
MUST has a vacancy for an academic researcher, that can be filled on any of the levels listed below, depending on the profile of the successful candidate. The incumbent will play a leading role in the research conducted in the MUST group and contribute to the overall success of the group. This includes participation in the group’s research programme through his/her research contributions, scholarly publications, postgraduate student supervision, and the execution of externally collaborative research projects.

JOB DESCRIPTION
KEY RESPONSIBILITIES:
(ASSOCIATE) PROFESSOR
Research
  • Lead and conduct high-impact research, aligned with the MUST Deep Learning research agenda.
 Postgraduate student supervision
  • Supervise Master’s and/or PhD students and/or postdoctoral fellows.
 Project contribution
  • Contribute to specific research and development projects: from the initial identification of projects to project delivery. Lead research and stakeholder interaction.
 Management
  • Contribute to the management of the MUST research group.
(SENIOR) RESEARCHER
Research
  • Conduct high-impact research, aligned with the MUST Deep Learning research agenda.
 Postgraduate student supervision
  • Supervise Master’s and/or PhD students and/or interns.
 Project contribution
  • Contribute to specific research and development projects: from the initial identification of projects to project delivery. Contribute directly to research outputs; assist with stakeholder interaction.
Management
  • Contribute to the management of the MUST research group.

Minimum requirements

PROFESSOR / ASSOCIATE PROFESSOR
  • An appropriate PhD (NQF level 10) in Computer Science, Engineering, or related field.
  • NRF-rated or a research portfolio that will qualify for NRF-rating within the next three years.
  •  A minimum of 10 years’ experience in conducting research in a higher education or industry context.
  • A minimum of 5 years’ experience in the theory and application of machine learning, with experience in deep learning-specific R&D a significant advantage.
  • Experience in the supervision of Master’s and PhD students.
SENIOR RESEARCHER
  • An appropriate PhD (NQF level 10) in Computer Science, Engineering, or related field.
  • A research portfolio as can be expected from a senior researcher.
  • Experience in conducting research in a higher education or industry context.
  • Experience in the theory and application of machine learning, with experience in deep learning-specific R&D a significant advantage.
  • Experience in the supervision of Master’s and PhD students.
KEY FUNCTIONAL/ TECHNICAL COMPETENCIES:
  • Excellent research skills and a sound publication record.
  • Proven competency in machine learning, deep learning and underpinning disciplines.
  • Strong programming skills, especially in Python and related machine learning libraries.
KEY BEHAVIOURAL COMPETENCIES:
  • Strong research orientation.
  • Critical thinking. Analytical and problem-solving skills.
  • Outstanding communication, planning and organisational skills.
  • Excellent work ethic, integrity and independence.
  • Self-motivated individual with strong interpersonal skills.

REMUNERATION
The annual total remuneration package will be commensurate with the level of appointment as advertised and in line with the NWU policy guidelines.
ENQUIRIES REGARDING JOB CONTENT MAY BE DIRECTED TO:                      Prof Marelie Davel (marelie.davel@nwu.ac.za)
ENQUIRIES REGARDING RECRUITMENT PROCESS MAY BE DIRECTED TO:   Mrs Fadilha Minty 018 299 4993
CLOSING DATE:                                                                                                    1 October 2023
COMMENCEMENT OF DUTIES:                                                                                Flexible (Nov. 2023 - Feb. 2024)
 
Kindly take note: applications may only be submitted online through the official nwu vacancy website.
Incomplete applications and those submitted through any other platform will not be considered.
 
The University subscribes to and applies the principles of the Employment Equity Act and is committed to transformation. Preference will be given to candidates from the designated groups, in accordance with the principles of the aforementioned Act and NWU Employment Equity Plan.
 
The University reserves the right not to make an appointment. If you are not contacted within two months from the closing date of this advertisement, please accept that your application was unsuccessful. Communication will be limited to shortlisted candidates only.

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