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-the-art mass spectrometry techniques, as well as develop or apply coding skills (R/Python) for large-scale data analysis. Your job responsibilities As Postdoc in cardiorenal metabolism your position
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companies. Writing well-documented, reproducible code and contributing to open-source Python packages released alongside the methods papers, including close collaboration with the second postdoc on a
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-time data into WRF-Chem • You will be contributing to the development of machine learning models used on data from Poleno Jupiters, applying Python and machine learning. • The position will focus
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science, geoscience, physics, engineering or a related discipline. Experience with quantitative data analysis and scientific programming, preferably in Python is required. Experience with
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multisensory systems, especially haptics (actuators, tactile displays, force feedback devices) Strong visual computing skills (Unity, C++/C#, Python, rendering, tracking or 3D reconstruction pipelines) A
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or energy systems. Experience with one or more process simulation and/or modelling environments (e.g. Aspen Plus/HYSYS, gPROMS, Modelica, Python/Matlab‑based frameworks) and an interest in working with
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species distribution models, joint/hierarchical community models, dynamic vegetation models, or related biodiversity forecasting approaches; advanced programming skills in R and/or Python and
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Experience with programming in Python, R, or similar languages Background in machine learning or deep learning methods Knowledge of genomics, transcriptomics, evolutionary biology, and plant biology is an
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level, which is in Danish). Scientific computing, possibly with different programming languages (e.g., Python, MATLAB/Simulink). Moreover, the candidate shall demonstrate the following experiences
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programming in Python, R, or similar languages Background in machine learning or deep learning methods, including Graph Neural Network (GNN) Experience with Large Language Models (LLMs) applied to