Tampere University announces a new Early Stage Researcher position on the topic of On-chip Photonic Deep Neural Network Components for Fast Image Processing.
Objectives: Photonic implementations of deep neural networks with the high-speed linear operation and low-loss high-bandwidth connectivity within the network. Develop components for an integrated end-to-end photonic deep neural network (PDNN) that performs sub-nanosecond image processing tasks. Develop the system optically performed linear computation and non-linear activation function. Develop a PDNN architecture that can be scaled to networks with a large number of layers, and a large number of inputs and demonstrate its application to plenoptic image processing tasks.
Expected Results: Direct, clock-less processing of optical data that eliminates analogue-to-digital conversion and the requirement for a large memory module, allowing faster and more energy-efficient neural networks for the next generations of plenoptic imaging systems.
Before applying, please make sure that you fulfil the eligibility criteria.
For more details on the position, the eligibility criteria, as well as the instructions for applying, please visit this website. The closing date for applications is the 1st of December 2022 (23:59 EET / UTC+2).