Research Assistant / Associate in Machine Learning for Complex Systems

Company description:

We are a world class research-intensive university. We deliver teaching and learning of the highest quality. We play a leading role in economic, social and cultural development of the North East of England. Attracting and retaining high-calibre people is fundamental to our continued success.

Job description:

The Role

In today's data-driven world, the complexity of systems in various fields—from healthcare to climate science—presents significant challenges for traditional analytical methods. Complex systems are characterised by numerous interconnected components, nonlinear interactions, and dynamic behaviors that are difficult to predict and manage. This complexity necessitates advanced tools and techniques to uncover patterns, optimize performance, and make informed decisions..

Join our dynamic interdisciplinary group and lead pioneering research to develop novel machine learning algorithms specifically designed for complex systems analysis.

Your role will offer a unique opportunity to work on groundbreaking projects that address real-world challenges, contributing to advancements in scientific knowledge and practical applications.

Dive into cutting-edge techniques such as deep learning, reinforcement learning, and Spiking Neural Networks (SNNs). Your work will involve analysing intricate datasets from engineering and scientific domains, utilising advanced data pre-processing methods to uncover significant insights. You'll be responsible for developing and validating computational models, optimising their performance through iterative experimentation. You will collaborate closely with domain experts to ensure your research is relevant and impactful. Document your findings, methodologies, and codebase for reproducibility, and contribute to prestigious peer-reviewed journals and conferences and present your work to non-specialist audiences. Assist in securing funding by preparing compelling research proposals and grant applications. Work alongside colleagues on interdisciplinary projects and support teaching activities within the School of Engineering, shaping the future of technology and innovation.

This appointment is full-time (37 hours) and fixed term until 31st August 2027. We would welcome requests for flexible working and depending on the needs of the role, blended working opportunities to work remotely as well as on campus may be considered.

To find out more about the role and view the job description, please click here.

To apply, please click on the Apply button above to complete an online application, upload a CV and a cover letter. Your cover letter is a supporting statement and should outline how you meet the essential criteria of the role.

For all informal enquiries, please contact Professor Daniel Coca, Head of School at: Daniel.Coca@newcastle.ac.uk.

Join the School of Engineering at Newcastle University and be part of a vibrant research community that is driving innovation and excellence. Our school offers state-of-the-art facilities, cutting-edge projects, and a collaborative environment that fosters interdisciplinary research. You'll work alongside world-renowned experts, contributing to groundbreaking advancements that address global challenges. With strong industry connections and a commitment to impactful research, our school provides opportunities for professional growth and the chance to make a real difference in the world.

For more information about the School of Engineering, and our research, please click here.

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