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The International Research Training Group (IRTG) 2445 ‘Temporalities of Future in Latin America: Dynamics of Aspiration and Anticipation’ is part of the Institute of Latin American Studies of Freie
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contract for 24 months. About you To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD qualified in dynamical systems or closely
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The Radiochemistry Unit, Department of Chemistry , is seeking a post-doctoral researcher to take part in a 3-year Research Council of Finland-funded project. The project concerns the study of
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30.05.2025, Wissenschaftliches Personal The Munich Institute of Robotics and Machine Intelligence (MIRMI) at the Technical University of Munich (TUM) is seeking outstanding candidates for one PhD
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dynamical systems. The position is part of the research project “A Rigorous Framework for Transient Random Dynamics”, funded by the Dutch Research Council (NWO). You will be part of a team with a PhD student
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if there are special grounds, for example, different types of statutory leave of absence. Applicants who are close to finishing a PhD are also encouraged to apply. Further information The position is fully funded by
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skills and desire to work as a member of a dynamic team, including collaborators internal/external to University of Dundee PhD in Biochemistry, Parasitology, Molecular Biology, or related field Experience
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systems (ITS). In particular, the successful candidate will conduct cutting-edge research in: Developing physics-informed neural networks (PINNs) for complex dynamical systems modeling and observer design
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Postdoctoral Researcher in Machine Learning of Isomerization in Porous Molecular Framework Materials
for isomerization in MOFs: https://doi.org/10.1039/D3QI01065A What we are looking for: A PhD in Chemistry, Materials Science, Physics or a related field Experience in python (ASE, scikit-learn, pytorch) is essential
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-flight measurements and defect spectroscopy Planning and realisation of 1D–3D device simulations with OghmaNano and machine learning to analyse charge carrier dynamics and loss mechanisms of organic solar