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- Tasks: Teach and research machine learning applications in engineering, focusing on information theory and communications.
- Company: Join the University of Sheffield, a world-class institution with a vibrant academic community.
- Benefits: Enjoy competitive leave, flexible working, generous pensions, and retail discounts.
- Why this job: Make a real impact in cutting-edge research and inspire the next generation of engineers.
- Qualifications: Strong publication record and expertise in machine learning, especially in information theory and communications.
- Other info: Be part of a diverse team driving innovation in defence, healthcare, and complex systems.
The predicted salary is between 36000 - 60000 £ 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.
The University of Sheffield is a remarkable place to work. Our people are at the heart of everything we do. Their diverse backgrounds, abilities and beliefs make Sheffield a world-class university.
We offer a fantastic range of benefits including a highly competitive annual leave entitlement (with the ability to purchase more), a generous pensions scheme, flexible working opportunities, a commitment to your development and wellbeing, a wide range of retail discounts, and much more.
We build teams of people from different heritages and lifestyles from across the world, whose talent and contributions complement each other to greatest effect. We believe diversity in all its forms delivers greater impact through research, teaching and student experience.
We invite applications from candidates who can contribute to the School's research and teaching activities in machine learning for engineering, with emphasis on information theory and communications as noted above.
Lecturer in Machine Learning for Engineering in Sheffield employer: University of Sheffield
Contact Detail:
University of Sheffield Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lecturer in Machine Learning for Engineering in Sheffield
✨Tip Number 1
Network like a pro! Attend conferences, workshops, and meet-ups related to machine learning and engineering. It's all about making connections that could lead to job opportunities.
✨Tip Number 2
Show off your expertise! Create a personal website or blog where you can share your research, projects, and insights in machine learning. This not only showcases your skills but also makes you more memorable to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on common questions in academia and industry. Be ready to discuss your research and how it aligns with the university's goals, especially in areas like information theory and communications.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets the attention it deserves. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Lecturer in Machine Learning for Engineering in Sheffield
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience in machine learning, especially in information theory and communications. We want to see how your background aligns with our needs!
Showcase Your Research: Don’t hold back on sharing your publication record and any independent research projects you've led. We’re looking for ambitious researchers, so let us know how you’ve made an impact in your field!
Be Clear and Concise: When writing your application, keep it straightforward and to the point. We appreciate clarity, so make sure your passion for teaching and research shines through without unnecessary fluff.
Apply Through Our Website: We encourage you to submit your application via our official website. It’s the best way to ensure your application gets into the right hands and helps us keep track of all the amazing candidates like you!
How to prepare for a job interview at University of Sheffield
✨Know Your Stuff
Make sure you brush up on the latest trends and developments in machine learning, especially in information theory and communications. Be ready to discuss your research and how it aligns with the university's goals. This shows you're not just knowledgeable but also genuinely interested in contributing to their work.
✨Showcase Your Teaching Skills
Prepare to demonstrate your teaching philosophy and methods. Think about how you can engage students in complex topics like machine learning. Maybe even prepare a mini-lecture or a teaching demo to showcase your style. This will help them see how you can contribute to their high-quality teaching environment.
✨Connect with Their Vision
Familiarise yourself with the university's strategic priorities and how your research can address critical challenges in areas like defence and healthcare technologies. During the interview, make connections between your work and their mission to show that you're a perfect fit for their vibrant research community.
✨Ask Thoughtful Questions
Prepare some insightful questions about the department's current projects, future directions, and how they support research initiatives. This not only shows your enthusiasm but also helps you gauge if the university is the right place for you. Remember, interviews are a two-way street!
