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collaborative environment. A team that believes in continuous learning and cultivates an environment of collaboration. Collaboration with research labs and other shared resources, including Molecular Genomics
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collaborative environment. A team that believes in continuous learning and cultivates an environment of collaboration. Once trained, flexible schedule What you’ll do: Operate equipment in the cagewash facility
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), proteomics (LC-MS/MS), (epi)genomic data processing, multi-omics integration, machine learning approaches for high-dimensional data, confocal / two-photon imaging, tissue clearing and light-sheet microscopy
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skills in data science, advanced AI interface development and machine learning?to apply climate change and other relevant data to real-world problems exchange and coordination with project partners Your
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information, military service, or other protected status.
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machine learning methods are a plus. Qualifications: PhD in neuroscience, or related fields DeepLabCut or similar methods Demonstrated hands-on experience with 2-photon imaging techniques Experience
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Engineering or a related field The ideal candidate should have some knowledge and experience in the following topics: Software Cybersecurity Software Testing and Analysis Machine Learning and Multimodal Large
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mechanisms and kinetics to stabilize highly active but metastable surface motifs sustainable catalytic processes. Modeling Atomic Processes on Nanoparticles Develop atomistic models and machine-learning
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measure gravitational effects on entangled photons for shining light onto the interface of quantum physics and gravity? Can we exploit quantum photonics technology for novel quantum machine learning
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-performance climate computing and data facility. Our expectations: outstanding scientific credentials and relevant research activities in high-performance computing, machine learning, or AI significant