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related field. Strong experience with Python, R, or C++ programming and high-performance computing (GPU/parallel workflows). A research track record including publications, presentations, or collaborative
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not intended to be a complete list of all responsibilities, duties, and skills required. Management reserves the right to revise the job or require different tasks to be performed as assigned to reflect
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multiple techniques. This will allow researchers to visualise and ‘manually weight’ different types of information from different sources globally and locally across a macromolecular structure, and pipe
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related field. You bring strong quantitative skills (e.g., R/Python, bioinformatics pipelines) and experience with high‑throughput sequencing and/or acoustic data analysis. You thrive in international
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geospatial data processing and python programming. Candidates should also have knowledge of optical, lidar, and ground penetrating radar sensing systems and understanding of pavement structures and condition
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Max Planck Institute for the Structure and Dynamics of Matter, Hamburg | Hamburg, Hamburg | Germany | 5 days ago
level of programming skills, including Python knowledge and its relevant libraries Outstanding communication skills and experience working with remote communication tools Experience in research software
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projects focused on studying the molecular mechanisms of arrhythmias with emphasis on conduction system diseases. To identify these pathways, the postdoctoral fellow will use mouse models for different
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Automated Generation of Digital Twins of Fractured Tibial Plateaus for Personalized Surgical plannin
currently relies solely on the surgeon’s expertise [2]. Unlike scheduled orthopedic procedures, trauma surgery has seen little integration of artificial intelligence in preoperative planning. Currently
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dimensional information, classification and/or deep learning methods may also be developed. In addition, the complementarity between the different data sources used (particularly between aerial LiDAR data and
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to trade in production. We don’t believe in “one-size-fits-all” modeling solutions; we are open to and excited about applying all different types of statistical and ML techniques, from linear models to deep