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Primary Responsibilities: - Design, and implement algorithms in Deep Learning for Medical Image Analysis problems - Work on large-scale data sets and real-world problems - Close collaboration with Siemens Healthineers Business lines to understand requirements and deliver successful AI solutions - Data analysis of clinical studies with clinical partners 主要職責(zé)： ? 設(shè)計(jì)并實(shí)現(xiàn)用于醫(yī)學(xué)圖像分析問(wèn)題的深度學(xué)習(xí)算法 ? 處理大規(guī)模數(shù)據(jù)集和實(shí)際的問(wèn)題 ? 與西門(mén)子醫(yī)療業(yè)務(wù)線密切合作，了解需求并提供成功的AI解決方案 與臨床合作伙伴進(jìn)行臨床研究的數(shù)據(jù)分析 Qualifications: - Ph.D. proffered in an engineering or science field such as Computer Science, Electrical Engineering, Statistics, or Applied Math. Alternative MSc. in an engineering or science field such as Computer Science, Electrical Engineering, Statistics, or Applied Math with at least 3 years experience - 2 years industry experience in building medical imaging solutions. - Strong background in Deep Learning and familiar with TensorFlow, PyTorch and etc. - Proficiency in Python and ability to quickly prototype in C is desired - Graduate research and internship experience in Computer Vision, Machine Learning and Image Understanding preferred - Experience in medical image and medical big data preferred - Outstanding written and verbal communication skills in English are required - Excellent interpersonal skills - Strong collaboration skills and ability to thrive in a fast-paced environment 要求： ? 計(jì)算機(jī)科學(xué)、電氣工程、統(tǒng)計(jì)學(xué)或應(yīng)用數(shù)學(xué)等工程或科學(xué)領(lǐng)域的博士學(xué)位。其他的理學(xué)碩士，在工程或科學(xué)領(lǐng)域，如計(jì)算機(jī)科學(xué)、電氣工程、統(tǒng)計(jì)學(xué)或應(yīng)用數(shù)學(xué)，至少3年工作經(jīng)驗(yàn)。 ? 2年以上解決醫(yī)療影像問(wèn)題的行業(yè)經(jīng)驗(yàn)。 ? 深厚的深度學(xué)習(xí)背景，熟悉TensorFlow、PyTorch等。 ? 精通Python，能夠在C 中快速實(shí)現(xiàn)的能力 ? 有計(jì)算機(jī)視覺(jué)、機(jī)器學(xué)習(xí)和圖像理解方面的研究生研究和實(shí)習(xí)經(jīng)驗(yàn)者優(yōu)先 ? 有醫(yī)學(xué)影像和醫(yī)學(xué)大數(shù)據(jù)經(jīng)驗(yàn)者優(yōu)先 ? 需要出色的英語(yǔ)書(shū)面和口頭溝通技能 ? 優(yōu)秀的人際交往能力 ? 強(qiáng)大的協(xié)作技能和在快節(jié)奏環(huán)境中茁壯成長(zhǎng)的能力