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new technologies to enhance the efficiency of excitation and detection of two-photon fluorescence from natural retinal chromophores. The aim is to enable precise fluorescence lifetime measurements and
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new technologies to enhance the efficiency of excitation and detection of two-photon fluorescence from natural retinal chromophores. The aim is to enable precise fluorescence lifetime measurements and
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the project is the development of AI-based pipelines for detecting, segmenting, and classifying lichen communities. Convolutional neural networks (e.g., U-Net, DeepLab) and machine-learning algorithms (e.g
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(pharmacy, medical analytics or related field), • knowledge of statistical methods used for data obtained by detection methods such as UV, DAD, MS, • intermediate level of spoken and written English