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Max Planck Institute for Solar System Research | Gottingen, Niedersachsen | Germany | about 1 month ago
Python. You will work in a newly formed team of two postdocs and a PhD student, led by the PI (Ekaterina Ilin), and collaborate closely with both postdocs, who will be working primarily on a large optical
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, computational biology, statistics or a closely related field. You have strong programming skills, preferably in Python, and experience with machine learning or deep learning. Experience in computer vision
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sources or related laboratory hardware. You are interested in instrument automation and quantitative data analysis. Experience with Python, LabVIEW, or Matlab for instrument control/data processing is
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to apply Website https://www.academictransfer.com/en/jobs/364001/phd-student-cerebellar-morpholo… Requirements Specific Requirements What you will be contributing We are looking for a researcher that a vivid
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. Solid programming skills (Python preferred; experience with PyPSA, MATPOWER, or similar modeling tools is a strong advantage). Reflective, analytical approach with aspirations to publish in high-impact
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highly motivated candidate with: Expertise in cell culture models Experience in molecular biology techniques such as qPCR, western blot, etc. Programming expertise in R and/or Python Comfort working in
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chirality, molecular ions, ultrafast optics, or instrumentation will be considered an advantage. Experience with Python programming is also preferred. MSCA Mobility and Eligibility Requirements As the
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wireless system. Analyse experimental measurements using MATLAB, Python or equivalent computational tools. Compare experimental measurements with modelling or theoretical predictions generated by the wider
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on machine learning and networks, release the code in open access and actively participate in the international interpretability community. Where to apply Website https://seuelectronica.upc.edu/en/procedures
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, particularly EEG; • Programming experience, particularly in R and Python; • Proficiency in statistical methods commonly used in psychology and neuroscience (ANOVA, linear models, etc.); • Familiarity with