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- Tasks: Lead innovative research in Machine Learning for Engineering and teach future engineers.
- Company: Join a world-class research university with a vibrant academic community.
- Benefits: 41+ days annual leave, flexible working, generous pension, and family-friendly policies.
- Why this job: Make a real impact in engineering while shaping the next generation of innovators.
- Qualifications: PhD in relevant field and strong publication record required.
- Other info: Be part of a diverse community that values unique perspectives and fosters inclusivity.
The predicted salary is between 48822 - 58225 £ per year.
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, complex dynamical systems, and healthcare technologies, areas of growth for the School and aligned with the UKRI strategic priorities.
Main 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).
Person Specification
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.
Criteria
- 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.
Further Information
- 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
Our Vision and What We Offer
- 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.
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.
Lecturer in Machine Learning for Engineering in Sheffield employer: The University of Sheffield
Contact Detail:
The University of Sheffield Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lecturer in Machine Learning for Engineering in Sheffield
✨Network Like a Pro
Get out there and connect with people in your field! Attend conferences, workshops, or even local meetups. Building relationships can lead to job opportunities that aren’t even advertised.
✨Show Off Your Expertise
Don’t just wait for the interview; start sharing your knowledge now! Write articles, give talks, or engage on social media about machine learning in engineering. This will position you as a thought leader and attract attention from potential employers.
✨Tailor Your Approach
When reaching out to potential employers, make sure to tailor your message. Highlight how your research aligns with their goals and how you can contribute to their projects. Personalisation goes a long way!
✨Apply Through Our Website
We encourage you to apply directly through our website. It’s the best way to ensure your application gets seen by the right people. Plus, you’ll find all the latest opportunities in one place!
We think you need these skills to ace Lecturer in Machine Learning for Engineering in Sheffield
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to highlight your experience in machine learning and engineering. We want to see how your background aligns with the role, so don’t be shy about showcasing your relevant publications and research.
Craft a Compelling Research Vision Statement: Your research vision statement should reflect your ambitions and how you plan to contribute to our vibrant research community. Be clear about your goals and how they align with the School’s focus areas, especially in information theory and communications.
Showcase Your Teaching Philosophy: In your teaching vision statement, share your approach to engaging students and fostering critical thinking. We’re looking for innovative ideas that can enhance our undergraduate and postgraduate programmes, so let your passion for teaching shine through!
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way to ensure your application gets the attention it deserves. Plus, we love seeing candidates who follow the process closely.
How to prepare for a job interview at The University of Sheffield
✨Know Your Research Inside Out
Make sure you can discuss your research in detail, especially how it relates to machine learning for engineering. Be prepared to explain the significance of your publications and how they contribute to the field. This will show your passion and expertise.
✨Prepare for Teaching Scenarios
Since teaching is a big part of this role, think about how you would design and deliver a module. Prepare a brief outline of a lesson plan or teaching strategy that showcases your ability to engage students and encourage critical thinking.
✨Showcase Your Leadership Skills
Be ready to discuss any leadership roles you've taken on, whether in research projects or teaching. Highlight how you've contributed to team dynamics and fostered an inclusive environment, as this aligns with the university's values.
✨Engage with Industry Connections
Think about how you can connect your research with industry partners. Be prepared to discuss any past collaborations or ideas for future partnerships that could enhance your research programme and benefit the school.
