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·計(jì)算機(jī)、電子電機(jī)工程、數(shù)學(xué)統(tǒng)計(jì)等相關(guān)專業(yè)，碩士或博士學(xué)歷| master degree or above in cs/ee, statistics or related field ·在計(jì)算機(jī)視覺(jué),機(jī)器學(xué)習(xí)或醫(yī)療影像領(lǐng)域的頂會(huì)或期刊上發(fā)表過(guò)論文| publications in top journals or conferences in the fields of computer vision, machine learning or medical imaging. ·精通機(jī)器學(xué)習(xí)和深度學(xué)習(xí)庫(kù)，如tensorflow或pytorch。對(duì)計(jì)算機(jī)視覺(jué)以及機(jī)器學(xué)習(xí)常見(jiàn)算法，模型和解法有深刻理解。| proficient with one of the popular deep learning software frameworks, such as tensorflow or pytorch. a deep understanding of common families of computer vision and machine learning models, algorithms, and solutions. ·了解計(jì)算機(jī)視覺(jué)和機(jī)器學(xué)習(xí)的一些新興技術(shù)（如圖像生成模型，多模態(tài)融合，小樣本學(xué)習(xí)，細(xì)粒度圖像分類，貝葉斯深度學(xué)習(xí)等）。understanding of emerging technologies in computer vision and machine learning such as generative models, multimodal fusion, few-shot learning, fine-grained classification, bayesian deep learning etc. ·工作有規(guī)劃條理，注意細(xì)節(jié)；有團(tuán)隊(duì)合作意識(shí)和溝通能力| detail-oriented, well organized and self-motivated with a continuous drive to learn, explore and be challenged; work well in teams and communicate ideas clearly ·有3年以上使用深度卷積網(wǎng)絡(luò)解決分類、目標(biāo)識(shí)別和分割問(wèn)題經(jīng)驗(yàn)優(yōu)先| prefer 3+ year(s) in using deep learning for classification, detection, segmentation, etc. ·有醫(yī)學(xué)影像經(jīng)驗(yàn)或視頻處理優(yōu)先| familiarity with videos or medical images is a plus

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