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advertisement Job description A three-year PhD fellowship in Neuroscience is available in the group of Dr. Matthijs Dorst (https://dorst-lab.org/ ), with co-supervision by Associate Professor Koen Vervaeke (https
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everyone can realize their potential is important to us. The following links provide further information on diversity and equal opportunities: https://go.fzj.de/equality and and on the targeted promotion
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transport experiments inside as well as a laser laboratory with Particle Image Velocimetry (PIV) and Laser-Induced Fluorescence (LIF) experiment capabilities. We are also in the process of expanding
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Recruiting-Portal, by submitting the following requested documents: A) a cover letter, B) a complete curriculum vitae C) the PhD application form, see https://www.zampierilab.org/join-us/ Where to apply
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development is important to us – we support you specifically and individually e.g., through training and networking opportunities specifically for doctoral candidates (JuDocS): https://go.fzj.de/JuDocs SUPPORT
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Mathematics (Inverse Problems), Computer Science (Machine Learning, Computer Vision, Efficient Algorithms and High-Performance Computing), and Physics (Image Formation Modelling). Your project is part of
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Max Planck Institute for Human Cognitive and Brain Sciences • | Leipzig, Sachsen | Germany | 2 days ago
TU Dresden or UCL may attend online. Application deadline See our website (https://imprs-coni.mpg.de/application-dates) for further information. Tuition fees per semester in EUR None Combined Master's
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viscoelasticity for cell culture, Rheological characterization of glioma and brain tissues as well as hydrogel systems, Microscopic imaging and measurements of traction forces generated by glioma cells cultured
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circuits in mouse models Applying tissue clearing techniques and light-sheet microscopy for 3D imaging of the entire mouse brain Analyzing and interpreting single-cell genomics data to investigate cellular
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. They have led to a plethora of important downstream applications, such as image and material generation, scientific computing, and Bayesian inverse problems. At the core of these models are differential