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Vacancies PhD Position on Neural Engineering/Computational Neuroscience/Biomedical Engineering Key takeaways We are seeking a highly motivated PhD candidate to join a multidisciplinary team working
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | about 1 month ago
Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Area of research: Scientific / postdoctoral posts Starting date: 01.12.2025
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? We invite applications for a PhD position, focusing on the design and implementation of Spiking Neural Networks (SNNs) using CMOS technology. Project Overview This PhD position is part of a
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motivated experimentalists who are deeply excited about working with nonhuman primates and connecting those results to computational models of the brain. The ideal candidates will enjoy hands-on neural
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advanced AI/ML methods to neural and behavioural data to uncover the computational foundations of decision-making in humans and animals. Designing novel AI algorithms inspired by brain function, to improve
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-responsive behaviour tasks using tasks that mimic biological learning principles and neuromodulation. Artificial neural networks with biologically-inspired dynamics will be trained and progressively pruned
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better ways to design neuromorphic or brain-inspired computing systems. These mechanisms must be energy-efficient, reconfigurable, and secure, especially for edge devices. This PhD project focuses
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/Qualifications Required qualifications: B.Sc. in life sciences. M.Sc. in life sciences. Enrolled as a student in a PhD Program in life sciences Oral & written skills in English language. Desired qualifications
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dynamical system modeling tools using specialized software packages to elucidate neural computations involved in emotion. Prepare and contribute to grant applications and conference presentations
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or equivalent Skills/Qualifications - PhD in bioinformatics or related subjects - Expertise in python coding - Experience and good understanding of neural networks and machine learning - Fluent written and spoken