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Field
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engineering, electrical engineering, data science, or a related field. Skills in embedded systems development, electronics, or IoT (C/C++, Python, Arduino/ESP32, etc.) OR in machine learning and sensor data
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described as intricate machines where proteins work together in a tightly coordinated fashion to produce essential cellular functions. Yet evolution challenges this picture. Proteins that are crucial for a
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Systems, or a related field. Strong analytical and critical thinking skills. Strong machine learning (ML), computer vision (CV), large language models (LLM) for quantitative data, texts, images, and sensor
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the opportunity to contribute to collaborative efforts at the interface of data science, imaging, and materials research. You will strengthen the data science and machine learning activities of the IAS-9 with
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algorithms for optimization Quantum annealing Quantum inspired optimization Quantum machine learning with a special emphasis on classical optimization of QML algorithms Noise mitigation in relation
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- and time-specific innervation that extends into adolescence. Our lab has used whole-brain tissue clearing, light-sheet imaging, and machine learning to map the spatial and temporal dynamics of serotonin
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transfer. We use complementary approaches including cryo-EM, biophysical methods and in vivo functional assays to study the protein machineries involved in this process. Join our young, ambitious, and
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within a Research Infrastructure? No Offer Description Topics In the Computer Systems Lab, we aim to hire multiple PhD students on national and international research projects in the domain of man-at
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expert knowledge in a reusable format. Numerical Representation, Develop numerical representations of ship designs that are interpretable by machine learning algorithms and suitable for generative ai model
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and curate LC-MS/MS data for high-quality feature extraction Design and train machine-learning models for mass spectrometry and chemometric data Integrate multi-omic data including genomics and