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Lecturer/Senior Lecturer in Data Science, Natural & Computing Sciences (NCS202A)

The School of Natural and Computing Sciences is looking to appoint a full-time staff at Lecturer or Senior Lecturer level in Computing Science to teach on a broad range of computing science lectures, laboratory classes and tutorials, and undertake administrative duties as necessary within the Aberdeen - South China Normal University Institute.  Appointees will primarily be based in Aberdeen, but will be expected to travel to China to deliver their teaching obligations; visits are likely to be up to 4 weeks duration at any one time.

School/Section: Natural & Computing Sciences
Division: Computing Science
Staff Category: Academic
Position Type: Full Time
Grade: Grade 7/8
Salary: £43,414 - £61,823
Ref No: NCS202A
Closing Date: 16-FEB-2023

Documents:

Job Description

Applicants should have research expertise in Data Science, and have the ambition to work across disciplines and with industry to achieve their research vision as part of the Aberdeen 2040 ‘Data & Artificial Intelligence’ challenge.

Candidates whose work is applicable to domains such as data management, cleansing and analysis, machine learning, statistical and causal methods, big data processing, pipeline optimisation, are particularly encouraged to apply. Successful applicants are expected to strengthen the School’s expertise in these areas. 

Key Responsibilities:

Research

  • To conduct cutting-edge research in fields of Computing Science closely related to the School’s strategic focus around Data Science
  • To prepare and submit manuscripts for publications in leading international conferences and journals.
  • To prepare and submit grant applications for external (e.g. UKRI) research support.
  • Take responsibility for the supervision and training of postgraduate research students.

Education

  • To contribute to the design, development, delivery, assessment and administration of a range of undergraduate courses delivered as part of the Aberdeen - South China Normal University Institute. This includes contribution to supervision of undergraduate dissertations within the Aberdeen - South China Normal University Institute.
  • To engage with modern pedagogical approaches to University teaching and implement best practice in teaching

Administrative & Support

  • To supervise students directly, providing a high standard of support and help.
  • To identify the learning needs of students and defining learning objectives.
  • To undertake administrative duties, as determined by the Head of School and Academic Line Manager.
  • Participating in the development and delivery of the School's strategic objectives

Lecturer salary will be at the appropriate point on the Grade 7,  (£43,414 - £51,805 per annum) and Senior Lecturer will be at the appropriate point on the Grade 8 (£54,949 - £61,823 per annum) negotiable with placement according to qualifications and experience.

Informal enquiries should be made to Dr Tryphon Lambrou, Interim Vice Dean for SCNU JI, e-mail:  tryphon.lambrou@abdn.ac.uk                                                                                    

Should you require a visa to undertake employment in the UK you will be required to fulfil the minimum points criteria to be granted a Certificate of Sponsorship under the requirements of the Skilled Worker visa.  At the time an offer of appointment is made, you will be asked to demonstrate that you fulfil the criteria in respect of qualification and competency in English. For research and academic posts, we will consider eligibility under the Global Talent visa. Please do not hesitate to contact Lucy Redmayne, HR Adviser (lucy.redmayne@abdn.ac.uk) for further information. 

To apply online for this position visit www.abdn.ac.uk/jobs 

Job Reference Number:  NCS202A 

The closing date for the receipt of applications is 16 February 2023 

The School of Natural & Computing Sciences embraces a diverse working environment and recognises the many benefits this can bring.  Applications from individuals from across all of the equality protected characteristics are encouraged.

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