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that can be used at speeds that are orders of magnitude faster than current CMOS technology. In order to demonstrate the computational power of so-called synchronised stochasticity for approximate Bayesian
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(photonics), electrical engineering or a related field? And would you like to be involved in research and development for detecting gas-phase contaminations in different novel/demanding applications
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teaching load may be up to 5% of your working time. Profile You have an MSc or BSc degree in neuroscience, cognitive neuroscience, psychology, computer science, physics, engineering, or a related field with
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, computer science, physics, engineering, or a related field with a strong quantitative background. You are enthusiastic about research and excel academically. You have excellent data analysis and statistics skills
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an enthusiastic young scientist who likes to work with and develop novel laser-based spectroscopy instruments? Do you hold a Master’s degree in physics (photonics), electrical engineering or a related