Lecturer in Data Science

York St John is an ambitious, modern university at the heart of historic York and there has never been a more exciting time to join us.

As one of the fastest growing universities in the UK over recent years, we have a new strategy for the next decade, emphasising our commitment to widening opportunity through the power of education and contributing our talents to creating a fairer world, and a more prosperous region. We are putting inspirational learning and impactful research at the heart of this strategy, recognising our academic expertise as our greatest asset.

The School

MSc Data Science clustered within the York London Campus, is an ambitious and growing academic unit. Our burgeoning national and international research profile, excellent teaching and learning, and welcoming and inclusive ethos supports an exceptional student experience (achieving (94%) and (91%) respective student satisfaction in the most recent NSS). Our School offers a number of Postgraduate degrees.

The role
We are seeking an enthusiastic Lecturer to contribute to our vibrant Postgraduate offers in MSc Data Science. The majority of your work will involve teaching in a variety of settings, including small group tutorials/seminars and lectures; assessment; and the provision of pastoral and academic support to students. The successful candidate will also be supported in developing a solid research profile. The main duties and responsibilities include:

• Develop and engage in high quality teaching, learning and assessment at postgraduate level 7 - MSc, including online and blended approaches.
• Contribute to the development of the subject discipline within the University through engagement in regular curriculum review activity that incorporates current knowledge and practice.
• Develop a teaching portfolio that reflects best practice and is regularly reviewed and refined through self-reflection, peer- support, student feedback and professional development.
• Participate in team meetings, peer review, appraisal, and other staff development activities, contributing to the development of academic programme.
• Undertake module leadership, mentoring, moderation work related to program management and assessment materials. Supervise postgraduate students on their Dissertation module.

Key requirements

Candidates will have expertise in teaching in any relevant field of Computer Science at Postgraduate level but in particular areas that complement data science such as big data, artificial intelligence, cloud computing, machine learning and cyber security. The successful candidate will be supported in cultivating an outstanding research profile in Data Science. Whilst we focus on areas including AI, Machine Learning, Big Data, Statistical Programming, Big Data and Cloud Computing, other research specialisms are welcome as we are keen to foster new connections.

A doctoral level qualification is desirable.

For informal enquiries please contact Dr Nalinda Somasiri at n.somasiri@yorksj.ac.uk

If you require a reasonable adjustment in order to apply for this position please contact vacancies@yorksj.ac.uk. Within the application form there is an opportunity for you to request a reasonable adjustment at the interview stage of the process, however if you wish to discuss this in further detail at any point in the process please do not hesitate to contact us.

We offer a wide range of employee benefits including -

• Excellent annual leave entitlement, including five discretionary university closure days over the Christmas period
• Pension scheme
• Health Cash Plan after six months service
• Employee Assistance Programme
• Relocation expenses package for certain roles

We offer a range of family friendly and inclusive policies and facilities to support staff from different backgrounds. As part of our commitment to providing an inclusive working environment, consideration is given to all requests for job share or flexible working arrangements. Find out more about our culture, working arrangements and benefits for York St John employees here.

Please note that CVs are not accepted in place of the application form.

Closing Date - Wednesday 26 April 2023 at midnight

Provisional Interview Date - Thursday 25 May 2023