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Deutsches Zentrum für Neurodegenerative Erkrankungen | Bonn, Nordrhein Westfalen | Germany | 1 day ago
to work independently in this area Experience with tissue processing, histological techniques, and microscopy Knowledge of image analysis tools (e.g., ImageJ, QuPath, or similar) is an advantage Structured
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/electronic engineering /mechanical engineering / computer science or related fields obtained in 2019 or later. 2. Experience in biophotonics imaging techniques. 3. Skills in image and signal
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& pathology/surgery. Strong foundational background in statistics and probability. Computer and web systems literate. Compensation, Benefits and Position Details Pay Range Minimum: $80,244.00 annual Pay Range
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operational leadership to support quality improvement initiatives, workforce development, technology planning, and the achievement of performance goals. The Manager works under the direction of senior imaging
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Eligibility criteria a. A PhD degree in Computer Engineering, Telecommunications Engineering, or related disciplines, or an equivalent degree obtained abroad. Pursuant to Article 38, paragraph 3 of Legislative
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reconstruction using Fourier domain optical normalization." Light-Science and Applications 5: el 60389, 2016. http://dx.doi.org/10.1038/Isa.2016.38 Henn MA, et al: "Optimizing the nanoscale quantitative optical
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Biology at Columbia University Irving Medical Center, through partnership with the NewYork-Presbyterian Hospital, established the Digital and Computational Pathology Laboratory (DCPL) in 2018 to accelerate
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an accredited agency is considered an asset. Proficient computer skills are essential, including experience with Microsoft and RedCap applications. Requires successful completion of a background check; qualified
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 6 days ago
Engineering, Computer Science, or Bioengineering. Knowledge of image processing and image analysis, preferably applied to medical imaging (e.g., segmentation, feature extraction, geometric reconstruction
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that are facile with computationally efficient, rigorous machine learning for image region identification, demonstrate an understanding of both planetary and scalable computer science, and have publication