Lecturer in Machine Learning for Engineering

The School of Electrical and Electronic Engineering seeks to appoint a Lecturer (equivalent to Assistant Professor) within the School’s Information and Communication theme and to build specialised expertise in the Machine Learning for Engineering sub-theme. Candidates from all areas in machine learning are encouraged to apply, with a special focus on the areas of (i) information theory and (ii) communications.

We seek ambitious researchers with a strong publication record and demonstrated potential to establish independent research programs of the highest calibre. Academic members will contribute to an environment of research excellence, scholarly activity, and high-quality teaching that will attract top students, world-leading researchers, and strategic industrial partners. The successful candidate will contribute to our vibrant research community and lead innovative research that addresses critical challenges in defence, and complex dynamical systems, and healthcare technologies, areas of growth for the School and aligned with the UKRI strategic priorities.

This is an opportunity to join a School in a world-class research intensive university, in your role as a Lecturer you will contribute to the School through the following duties and responsibilities:

• Conduct personal research of international standing independently and collaboratively.
• Maintain a strong academic and professional profile through national and international engagement and high quality publications.
• Develop an internationally leading research program, and engage with industry and policy partners shaping the future of engineering and science.
• Secure external funding to support future research activity and build an independent research group.

• Design, develop and deliver teaching on modules across a range of undergraduate and postgraduate programmes, including coordinating team teaching to ensure high quality delivery; preparing teaching material, communicating subject matter and encouraging critical discourse and rational thinking; observing and reacting to student interventions; responding to questions outside class times and to contingencies in module delivery.
• Carry out assessments for modules, including designing assessment instruments and criteria; marking assessments, ensuring adequate moderation; providing written/oral feedback; and collating and providing final assessments of students.
• Supervise and assess UG and PG dissertation students and doctoral students.
• Carry out module evaluation, including facilitating student feedback; reflecting on own teaching design and delivery; and implementing ideas for improving own performance.

• Contribute to the life of the School, Faculty and wider University community by taking on leadership roles and responsibilities where required, and contributing to committee work and the development of relevant policies.
• Make ethical decisions in your role, modelling inclusive and collegiate behaviour, and embedding the University’s sustainability strategy into your working activities wherever possible.
• Contribute fully as a researcher, teacher and leader, fulfilling the appropriate requirements of the University’s Academic Career Pathway Framework (ACP).

Our diverse community of staff and students recognises the unique abilities, backgrounds, and beliefs of all. We foster a culture where everyone feels they belong and is respected. Even if your past experience doesn\'t match perfectly with this role\'s criteria, your contribution is valuable, and we encourage you to apply. Please ensure that you reference the application criteria in the application statement when you apply.

• CV (including a list of publications)
• Research Vision Statement
• Teaching Vision Statement
• A statement of published outputs in which you identify your three best peer reviewed publications. For one of these you should provide a short statement of no more than 100 words describing the originality, significance and rigour of the paper.

Essential Or Desirable

Stage(s) assessed at

• Have completed a PhD (or have equivalent experience) in a relevant research area related to Information and Communication Technologies for Engineering (Machine Learning for Engineering).
• Research experience as evidenced by a good publication record/the ability to publish high quality research in peer reviewed journals.
• Experience of preparing grant applications for submission, including clear and feasible plans to secure research income from a variety of funding streams.
• Ability/potential to develop and lead an independent research group in a relevant research area.
• Experience of training/developing undergraduate and postgraduate students with successful outcomes.
• Ability to develop, deliver and assess high-quality teaching at a variety of levels.
• Ability to communicate well, conveying ideas and concepts clearly and effectively as well as a high level of analytical capability.
• Good leadership skills and ability to work in a multidisciplinary team.
• Being supportive and inclusive when communicating and working with colleagues, students and external collaborators.

• Grade: Grade 8
• Salary: £48,822-£58,225 per annum (with the potential to progress to £65,509 per annum)
• Work arrangement: Full time
• Duration: Open Ended
• Line manager: Academic Line Manager
• Direct reports: n/a

• A minimum of 41 days annual leave including bank holiday and closure days (pro rata) with the ability to purchase more.
• Flexible working opportunities, including hybrid working for some roles.
• Generous pension scheme.
• A wide range of discounts and rewards on shopping, eating out and travel.
• A variety of staff networks for development and support.
• Recognition Awards to reward staff who go above and beyond in their role.
• A commitment to your development with access to learning and mentoring schemes; integrated with our Academic Career Pathways.
• A range of generous family-friendly policies, including paid time off for parenting and caring emergencies, menopause support, fertility treatment support, and more.

More details can be found on our benefits page: sheffield.ac.uk/jobs/benefits (opens in a new window).

We are a Disability Confident Employer. If you have a disability and meet the essential criteria for this job you will be invited to take part in the next stage of the selection process.

We are a research university with a global reputation for excellence. Our ideas and expertise change the world for the better, making a real difference to society. We know that when people come together with different views, approaches and insights it can lead to richer, more creative and innovative teaching and research and the highest levels of student experience. Our University Vision outlines our commitment to building a diverse community of staff and students that recognises and values the abilities, backgrounds, beliefs and ways of living for everyone.