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and software for high-throughput retinal recordings, to conduct the respective measurements, as well as to further develop the data-evaluation and signal-analysis pipeline. The work will be performed in
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temporal scales - in both terrestrial and aquatic ecosystems, their origination and their response to global changes. To make these connections, we collect data through environmental DNA methods, remote
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filled. For more information about our group, please visit our website . Profile We welcome applications from candidates with expertise in one or more of the following areas: Organic synthesis
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The Population Mental Health Risk Prediction via Linkage of Multi-Modal Spatiotemporal Environmental Data To Population-Representative, Longitudinal Clinical Measures of Individual Mental Health (PRISMS) project
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students. The institute has also published at most of the major machine learning, computer vision, and robotics conferences, including CVPR, NeurIPS, ICCV, ECCV, ICML, ICLR, IROS, AISTATS, as well as in
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Apply machine learning techniques for data analysis and time-series forecasting Collaborate in a multidisciplinary team to accelerate functional thin film development Your work will be part of a larger
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handling: isolation, fixation and vibratome sectioning for immunostaining. AI-assisted image analysis for spatial analysis of tissue samples. Multidisciplinary team work, with immunologists, data scientists
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knowledge graphs into a simulation-as-a-service middleware. Performing software engineering and data management tasks in support of the realisation of this architecture. Exploring and evaluating different
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intelligence (AI) techniques for wind and solar energy production. The research framework will involve data collected from various wind and solar power plants in Switzerland and worldwide. By using long time
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field with a strong experimental background in frequency-locked lasers or optoelectronics. Experience with dual-comb laser spectroscopy is advantageous. Hands-on experience with data acquisition and