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based techniques to analyse spike train recordings to advance our understanding of neural population coding while maintaining clarity in the interpretation of results. Concurrently, AI-based methods
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Leipzig Website https://www.ufz.de Street Permoserstraße 15 Postal Code 04318 E-Mail info@ufz.de Phone +49 341 6025 1269 Fax +49 341 235-2649 STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp
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Your Job: This PhD project bridges between classical analytical methods and modern AI based techniques to analyse spike train recordings to advance our understanding of neural population coding
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for information-driven experiment steering (closed-loop control) Work in an interdisciplinary team of engineers, computer scientists, and life scientists Present your work at international conferences and learn
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Your Job: Energy systems engineering heavily relies on efficient numerical algorithms. In this HDS-LEE project, we will use machine learning (ML) along with data from previously solved problem
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mentorship in the career development of the student. The program language is English. We offer: a highly international research environment and state-of-the-art technology four years of full funding through
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the experimental data and the concepts of neuronal coding, and Elephant Analysis of the parallel rate data for submanifolds and their temporal dynamics during behavior Leverage dimensionality reduction and
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interdisciplinary team of engineers, computer scientists, and life scientists Regularly participate in international conferences to present your own work, and learn about state-of-the-art machine learning and
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, energy systems, or material sciences A Masters degree with a strong academic background in mathematics, computer science, physics, material science, earth science, life science, engineering, or a related
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of results through high-quality publications and open-source software contributions Your Profile: Master’s degree in chemical engineering, biotechnology, computational biophysics, bioinformatics, data science