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Field
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The main task is the further development of methods for the non-destructive investigation of the pyramids of Giza in Egypt (World Cultural Heritage) in cooperation with our partners by using acoustic imaging
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research program focused on spatial immuno-oncology, utilizing cutting-edge technologies (e.g., spatial transcriptomics, spatial proteomics, imaging mass cytometry) to study the tumor microenvironment
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positively valued: programming languages (Python, JavaScript), data analysis software techniques and tools, machine/deep learning (Pandas, SHAP , TensorFlow, etc.) and specific to image analysis, statistics
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to accelerate TBI research. This individual will have experience with designing, implementing, and interpreting human clinical studies of TBI including magnetic resonance imaging, blood-based biomarkers, and
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paradigm for quantum optimization with quantum computing (QAOA, Quantum annealing, etc.) Knowledge of quantum computing SDKs such as Qiskit or Pennylane We offer Multilingual and international character
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Description Job Summary: Under nominal direction, this individual performs a variety of basic and general laboratory research and clerical tasks related to fluorescence imaging of dynamic cellular processes in
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spatial omics datasets. The position will also contribute to multi-modal data integration efforts that combine imaging, genomics, and machine learning approaches. Key Responsibilities Data Processing
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influence brain and heart health. Responsibilities will involve recruiting participants, screening participants for eligibility, scheduling participants, collecting physiological and brain imaging data (MRI
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Research Institute for Environmental and Occupational Health (IRSET - UMR_S INSERM 1085) | Rennes, Bretagne | France | about 2 months ago
such as molecular biology, flow or spectral cytometry, immuno-histochemistry, inflammatory signaling pathways, cell culture, imaging, and multi-omics analysis. Knowledge of environmental exposures and their
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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