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of organic and inorganic molecules encapsulated inside 2D materials. As a PhD Student, you will become part of an excellent scientific network and benefit from our structured, interdisciplinary graduate
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- ideally experience with collaborative software development, e. g. by having contributed to open source projects - willingness to adapt to an existing code structure - open and reliable personality, ability
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with significant documents (motivation letter, CV, transcript or records), indicating the reference code, in PDF format (preferably as one document) to Prof. Dr. Céline Teney: bewerbungen-ifs@polsoz.fu-berlin.de
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Your Job: In this project, we will incorporate non-linear input integration mimicking dendritic dynamics into spiking neural networks. This will involve: Designing dendritic modules in PyTorch
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on an important topic in a well-funded multi-disciplinary international training network. The training involves multiple activities, in addition to your research, and secondments across our partners. Overview
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Responsibilities: The successful applicant will cover research and teaching in the field of data-driven material research with a reduced teaching load of two weekly credit hours at Freie Universität Berlin. The professorship includes the opportunity of establishing and leading a newly founded...
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The Planetary Sciences and Remote Sensing research group at the Institute of Geological Sciences at the FU Berlin participates in various experiments in space missions of ESA, NASA and JAXA. In our two laboratories we generate analogue data for space missions with astrobiological mission...
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Responsibilities: The successful applicant will cover research and teaching in the fields of biodiversity and conservation genomics at Freie Universität Berlin and co-direct the Berlin Center for Genomics in Biodiversity Research at the Leibniz Institute for Zoo and Wildlife Research...
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code, in PDF format (preferably as one document) to Swantje Hartmann-Rolke: s.hartmann-rolke@fu-berlin.de or postal to Freie Universität Berlin Fachbereich Physik Institut für Theoretische Physik Frau
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of Convolutional Neural Networks (CNNs) and Spiking Neural Networks (SNNs), with a strong emphasis on deploying these models on hardware-constrained edge platforms. The position focuses on developing robust