35岁以下；博士毕业不超过3年；学校认定的A类文章至少1篇（文）/中科院2区以上文章至少一篇（理）；获得世界排名前100名的高校（不含境内，排名以2016年泰晤士报高等教育复刊为准）博士学位者优先考虑。
注：博士后年薪总收入20-45万，包括学校固定薪酬待遇和研究所绩效奖金。
中美国际联合团队
博士后
研究方向：必须为生物医学信息类等相关领域，且熟悉数据挖掘算法 (详见附录)；
工作地点：美国堪萨斯大学医学信息中心；
注：薪酬按照美国政府博士后薪酬水平规定发放
应聘材料
发送中文个人简历以及2至5篇代表性论文至邮箱：bddi.jnu@foxmail.com，邮件主题注明：应聘职位+专业+本人姓名，初审合格者将及时通知面试。
联系方式
联系人：莫老师、张老师、胡老师
电 话：020-85223261
邮 箱：bddi.jnu@foxmail.com
地 址：广州市黄埔大道西601号暨南大学第二文科楼10楼
研究所网站：https://bddi.jnu.edu.cn
附录: 中美国际联合团队博士后招聘详情
The Division of Medical Informatics at the University of Kansas Medical Center (KUMC) is seeking a highly ambitious, independent and motivated individual with a passion in data-driven knowledge discovery for improving patient outcomes and care to join as a Postdoctoral Fellow. At KUMC, you will be part of a rapidly growing team developing informatics methods to further biomedical research (KUMC received the NIH Clinical and Translational Science Award in 2011 and our division is leading the Greater Plains Collaborative, a PCORnet Clinical Data Research Network uniting 12 medical centers across 9 US states; over 20 million patients as well as over 20 million claims beneficiaries). You will have the opportunity to work in close collaboration with clinicians, scientists, and healthcare systems with access to deep clinical data warehouses (e.g. electronic medical records (EMR), billing, claims, and over 50 million unstructured notes), capability for implementing AI-based clinical decision support systems in the EMR, and professional development resources such as grant writing workshops and clinical shadowing experiences.
The successful candidate will be part of an interdisciplinary research team focused on predictive modeling and actionable knowledge discovery with a special clinical focus on kidney disease.
Required Qualifications:
• PhD in related fields including biomedical informatics, computer science, information science, data science, applied mathematics, (bio)-statistics, or physics
• Expert in one or more programming environments, including R, Python, SQL
• A track record of completed research projects with peer reviewed publications
• Excellent written and oral communication skills
• Expected to participate in both independent and collaborative projects
Preferred Qualifications:
• Training in biomedical informatics, machine learning, deep learning, and data science
• Experience with EMR or claims data extraction, cleaning, and analysis
• Experience with Natural Language Processing (NLP)
• Data integration such as geocoding to incorporate social determinants of health or other sources to inform predictive and explanatory models
• Ability to communicate effectively with diverse stakeholders including clinicians, IT staff, basic scientists, and translational researchers
Specific responsibilities and research projects will be tuned to the career goals, technical strengths, and interests of the applicant.
How to Apply:
