Research Fellow

About HiPPo

Fibre lasers are now routinely used in the most advanced production lines for cutting, welding, 3D printing, and marking of a myriad of materials from glass to steel. The ability to precisely control the properties of the output laser beam and to focus it on the workpiece makes fibre lasers indispensable to modern manufacturing. As we enter the Digital Manufacturing/Industry 4.0 era however, new challenges and opportunities for fibre lasers are emerging.

The primary objective of the HiPPo project www.hippo-laser.co.uk) is to move beyond the “fixed” fibre lasers that are currently used in manufacturing, and towards “smart” fibre lasers that are automatically reconfigured and optimised in real-time depending on the application. This ambitious objective requires research breakthroughs across the spectrum of fibre laser development, from the development of new fibre core materials, to addressing limits imposed by instabilities, noise and nonlinearities, to high-speed beam and polarisation shaping, and finally using deep learning to solve the complexity challenge associated with coherent beam combination.

The role

Within HiPPo, your specific task will be to develop a ‘digital fibre laser’, through the neural-network control of a tiled array of fibre lasers in a coherent beam combination architecture, for unlocking novel scaling and beam shaping capabilities in real-time. You will work at the Optoelectronics Research Centre (www.southampton.ac.uk/about/faculties-schools-departments/optoelectronics-research-centre) in a project team of currently nine Research Fellows and a similar number of PhD students focussed on delivering the next generation of fibre lasers. You will have access to our state-of-the-art cleanroom facilities, and be led by a team of world leading experts in the fibre laser and deep learning domains. 

About you

You will have a PhD in an experimental discipline or equivalent experience, ideally with experience in fibre optics and low-noise lasers and optical amplifiers, along with their practical implementation. Applications are also welcome from candidates nearing completion of a relevant PhD qualification. Whilst this is a laser development role, awareness of deep learning techniques is beneficial as you will be working closely with deep learning specialists.

What we offer 

The University of Southampton is in the top 1% of world universities and in the top 10 of the UK’s research-intensive universities. We are committed to sustainability and being a globally responsible university. We have recently been awarded the Platinum EcoAward, and strive to embed sustainability into all aspects of our individual and collective work. We aim to create an environment where everyone can thrive and are proactive in fostering a culture of inclusion, respect and equality of opportunity. With a generous holiday allowance, we are committed to supporting our staff and are open to flexible working.

To informally discuss the position, please contact Prof Johan Nilsson (jn@orc.soton.ac.uk). Please quote the advert reference on all correspondence.

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