We at Siemens Healthineers? are committed to helping healthcare providers globally to succeed in today’s dynamic environment. We are inspired to transform the way things are done – because we want what is best for our people, our customers and ultimately the health of mankind. While we are invested in engineering excellence – leading-edge medical technologies and services, we don’t stop there. We’re also deeply invested in our 46.000 people with the
hearts of pioneers and minds of engineers, highly committed and connected in this industry. And as we strive to shape the future of healthcare, our overall success will depend on our ability to continuously reinvent ourselves.

If you are ambitious and change makes you thrive, help transform Siemens Healthineers into a learning organization.
?研究，設(shè)計，實施人自然語言處理算法（包括相關(guān)的人工智能深度學習），用來解決醫(yī)學影像報告分析中遇到的問題；
?進一步提高前沿算法；
?解決大規(guī)模實際問題，高速建模和可行性預(yù)研。

This position may suit you best, if building learning organizations is your expertise and you have extensive experience with Top Management Learning and Leadership Development.
?有很強的自主研究，C++, Python編程能力；
?有計算機視覺，機器學習經(jīng)歷，能夠基本理解醫(yī)學影像和報告；
?有人工智能平臺編程經(jīng)驗，接觸過工具Caffe, Tensorflow, PyTorch等；
?流利的中英文讀寫；
?很強的團隊協(xié)作精神，能在快節(jié)奏中出成績。
加分項：
?有人工智能相關(guān)算法大賽經(jīng)驗；
?最好有計算機科學，電子/計算機工程，生物醫(yī)學工程，統(tǒng)計或應(yīng)用數(shù)學的博士學位。如果是相關(guān)領(lǐng)域碩士，需要有3年工作經(jīng)驗，其中1年以上人工智能算法編程經(jīng)驗；
?編寫過基于GPU的CovNet, GAN, Reinforcement Deep Learning，LSTM，Word2Vec, GloVe, Seq2Seq等模型；
?在相關(guān)國際期刊或會議上發(fā)表過論文。