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Field
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software. Familiarity with deep learning platforms (e.g. TensorFlow, PyTorch). Funding and eligibility The project is fully funded by DSTL, due to funding requirement this studentship is only available
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Germany | 3 months ago
immunology with deep focus on T cells and Treg biology Hands-on experience with in vivo mouse models (FELASA certification is a strong plus) Practical experience in flow cytometry (FACS), including protocol
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analytical and problem-solving skills. Good written and spoken English. Desirable: Experience with photonic/electromagnetics simulation software. Familiarity with deep learning platforms (e.g. TensorFlow
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the mechanobiology of native and engineered tissues, with a current focus on cardiovascular applications, using integrated computational and experimental methods. The group focuses on developing a deep understanding
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Are you interested in exploring how multi-agent aerial manipulation can contribute to construction and working at the intersection of robotics and machine learning? Job description Advancements in
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, clinical data and AI-driven modelling for cancer research! In this role, you will bridge the gap between machine learning, computational biology, and haematological oncology. You do not need to arrive as an
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research environment A self-motivated, proactive, and self-driven working attitude Curiosity-driven self-learning ability Written and oral communication skills in Dutch Keep in mind that this describes
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diagnostics and individualized treatment strategies by uncovering molecular mechanisms that drive bleeding severity. As a PhD student, you will contribute to our consortium by performing deep phenotyping based
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to plant biosciences where the impact could be huge and as a result exciting opportunities get missed. When we use light to image deep into complex samples there is a common problem that occurs – the light
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and ability to communicate clearly Merits include: Knowledge of LLMs, deep learning, and Python programming Knowledge of power electronics Experience in modelling, simulation, and experimental work In