Machine Learning Researcher – London

What you’ll do:

• Lead the development and refinement of novel machine learning architectures and algorithms harnessing our nonlinear dynamics. Building deeper network architectures that maximise efficiency and performance.
• Design, build and test models both on device and using in-house simulation framework.
• Collaborate closely with the wider photonics and hardware team to design and evaluate general metrics to assess the computational properties of the hardware and optimise for computational performance.
• Research state-of-the-art machine learning & machine vision techniques and adapt them to be compatible with our hardware.

Experience

• Proven track record of developing novel algorithms (papers in NeurIPS, ICML, ICLR, CVPR, or Nature/Science journals)
• Hardware Aware ML / Neuromorphic Computing:
• FPGAs, ASICs, analog computing chips, spiking neural network (hardware), edge AI
• Unconventional training algorithms
• Reservoir computing, self-constrastive learning, forward-forward learning, evolutionary algorithms, equilibrium propagation
• Physics informed neural networks, or applied ML to physics problems
• Deep understanding of mathematics, algebra / topology – key words are latent space, intrinsic dimensionality
• Experience working with hardware as well is a bonus

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