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Field
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Assistant in Python / 3D Gaussian Splatting. Become a part of our team and join us on our journey of research and innovation! Be part of change • Further development of our 3D gaussian splatting/processing
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | about 6 hours ago
analysis workflows. Program and implement statistical methods using R and Python. Design and deliver online teaching materials and training workshops for scientists. Supervise and train PhD students and
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pipeline in Python (using e.g. PyTorch) validation of your results in collaboration with colleagues from various application areas (cross-disciplinary) publication and presentation of your scientific results
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ETHOS.HiSim, a python package to simulate households and building systems. Identification of techno-economic data for buildings, retrofitting options, heating and cooling systems, and the building stock
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modeling, and eye tracking is expected. Strong skills in experimental methods, quantitative analysis, statistics, and programming languages such as R, Matlab, or Python are highly desirable. Responsibilities
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quantitative data and ideally historical data sources - Knowledge of descriptive statistics and statistical software (e.g. R, stata, Python) - Interest in economic sociology and political economy - Knowledge
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Engineering, or a related discipline - Solid understanding of fluid dynamics and/or electromagnetism - Programming experience (preferably Python) - Interest in machine learning and scientific computing
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | about 6 hours ago
skills (Python/R/Bash) and Linux. Experience with workflows, version control (Git), and scientific computing. Problem-solving mindset and good communication skills. Fluent in English. Desired Skills HPC
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Python-based) Test and benchmark the model with trained and untrained data Compare the ML models with traditional feature extraction methods and evaluate their success rate Your profile Enrolled in a
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evaluate usability of system architectures such as Retrieval-Augmented Generation (RAG) for data retrieval and knowledge inference - implementation of your machine learning pipeline in Python (using e.g