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Field
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programming ability in Python, and practical experience with a modern deep learning framework such as PyTorch. Experience working with 3D data in some form: volumetric images, meshes, point clouds, or geometric
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analyze multi-omic data provided by our collaborative partners and interpret the results from a biologically relevant perspective. Planned activities include Python code development, the analysis and
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background in experimental design, data analysis, and scientific writing. Proficiency in statistical software (e.g., R, SPSS, Python) and survey tools (e.g., Qualtrics). Ability to work independently and
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/instruction tuning methods. * Understanding of Reinforcement Learning (RL) principles, multi-objective optimization, or active learning/Bayesian optimization. * Strong programming capabilities in Python
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of experience within the field. Scientific and numerical programming in Python or R and knowledge of class ML methods and deep learning methods. Well versed in a variety of bioinformatic analyses, including Next
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of statistical and quantitative methods for analyzing complex, highdimensional datasets Good understanding of biochemical principles, including mass spectrometry Good programming skills (Python and/or R) Strong
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quantitative microscopy (live-cell imaging, high-content screening, or single-cell/single-bacterium imaging) Comfort with image analysis pipelines and scripting (Python), experience integrating ML-based image
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magnetic resonance imaging (MRI), such as arterial spin labeling and diffusion tractography using programming scripts, such as Python and C++ Self-driven, motivated, and creative in designing image analysis
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experience using statistical software such as R, Stata or Python, together with the ability to manage and analyse complex datasets and contribute to scientific publications and presentations. You will also
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hold a Ph.D. in materials physics or scientific imaging, with proven experience in spectral imaging techniques (e.g., software such as Python, R, HyperSpy) and/or synchrotron techniques (luminescence, UV