牛津大学高等研究院(苏州)招聘医疗人工智能研究员

近日牛津大学高等研究院(苏州)

发布医疗人工智能研究员招聘信息

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牛津大学高等研究院(苏州)(OSCAR)招募医疗人工智能研究员。The Oxford Suzhou Centre for Advanced Research (OSCAR) is seeking to recruit a Research Scientist in AI for Healthcare.

招聘岗位 The role
医疗人工智能研究员Research Scientist in AI for Healthcare

在人口持续增长、患者合并症不断增加的时代背景下,医疗健康行业迫切需要基于人工智能的可靠智能系统提供临床支持。牛津大学计算健康信息(CHI)实验室(https://eng.ox.ac.uk/chi)及其苏州研究组是国际知名的医疗人工智能研究机构,专注于发展基于机器学习方法的下一代临床人工智能系统。任职者将加入牛津大学高等研究院(苏州)(OSCAR)数字健康研究组,在CHI实验室中担任重要职责,并在牛津大学工程科学系David Clifton教授(英国皇家工程院讲席教授)(https://eng.ox.ac.uk/people/david-clifton)的指导下,与牛津大学医院NHS信托基金会、中国医疗机构等临床合作伙伴开展研究工作。

OSCAR在科技成果转化方面成绩斐然,已成功孵化多家衍生/初创公司。任职者的研究成果将有机会通过技术许可或创建衍生公司等方式实现商业化。OSCAR建立了完善的激励机制,通过专利收益分配、股权激励等形式回馈参与研究人员。

该职位的研究工作将聚焦于大规模临床数据的机器学习分析,涵盖时间序列生理数据、实验室检测数据、药物干预及临床诊断等多个维度,欢迎拥有人工智能、机器学习、大语言模型、基础模型、信号处理、计算统计学或生物医学工程等研究背景的申请者。

任职者将与牛津大学CHI实验室保持密切合作,并有机会赴牛津进行学术交流访问。该职位作为连接中国与世界顶尖学府的学术平台,可为优秀任职者提供晋升至牛津大学CHI实验室博士后岗位的独有学术发展机会。

There is an urgent, unmet need for reliable, intelligent systems based on AI for supporting clinicians in delivering healthcare to an ever-increasing population with increasing comorbidities. The Computational Health Informatics (CHI) Lab (https://eng.ox.ac.uk/chi) at the University of Oxford and its Suzhou site is building the next generation of healthcare systems for use in hospitals and the home, based on machine learning.The post-holder will take a major role in the research activity of the CHI Lab within the Oxford-Suzhou Centre for Advanced Research (OSCAR) site at Suzhou, China, under the overall supervision of Prof. David Clifton (https://eng.ox.ac.uk/people/david-clifton), Royal Academy of Engineering Chair of Clinical Machine Learning at the Department of Engineering Science, University of Oxford. Research will be undertaken in collaboration with clinical colleagues in the Oxford University Hospitals NHS Foundation Trust and other collaborators, including those based in China.

OSCAR has a strong track record in commercialising its research outcomes, including the creation of spin-out/start-up companies. Research outcomes from the programmes on which the post-holder would work would be considered for licensing and spin-out activity as appropriate. OSCAR recognises researchers involved in such work via royalty streams, potential equity in resulting companies, etc.

The work will comprise machine learning research for analysing large-scale clinical data, including time-series physiological data, blood test data, medications/interventions, and clinical diagnoses. The post would be suitable for applicants with general interests in AI, machine learning, large language models, foundation models, signal processing, computational statistics, and biomedical engineering.

The post will involve liaising closely with the Oxford-based lab, including exchange visits to Oxford. In particular, this post represents a uniquely promising career pathway, offering the post-holder the opportunity to advance to a postdoctoral researcher position at the CHI Lab, University of Oxford, and to bridge research experience between China and one of the world’s leading universities.

PI简介
David Clifton教授现任英国牛津大学临床机器学习教授、英国皇家工程院讲席教授、英国国家健康研究所讲席教授、以及牛津大学高等研究院(苏州)首席科学家。他领导的牛津大学计算健康信息(CHI)实验室是世界上规模最大且最具影响力的医疗人工智能研究团队之一。他是国际工程技术学会会士、英国阿兰图灵研究所会士、牛津大学鲁本学院人工智能与机器学习会士,并担任国际学术期刊IEEE Rev Biomed Eng和IEEE J Biomed Health Inform的副主编。他发表学术论文逾400篇,论文总引用超过26,000次,H-指数77,持有30多项相关专利,孵化了6家牛津衍生公司,其中1家已于伦敦证交所上市。他获得了超过35项奖项,包括英国维康信托基金会“发现奖”、IEEE“早期生涯奖”(全球每年仅授予一人)、首届牛津大学“校长创新奖”、EPSRC“未来医疗健康领袖奖”以及英国国会授予的“科学工程技术奖”等。
PI Biography
Professor David Clifton is the Royal Academy of Engineering Chair of Clinical Machine Learning at the University of Oxford, and leads the Computational Health Informatics (CHI) Lab, which focuses on “AI for Healthcare”.  He is also a NIHR Research Professor, appointed as the first non-medical scientist to the NIHR’s “flagship chair”. He is a Fellow of the Alan Turing Institute, a Fellow of IET, the PI of the Digital Health Group, OSCAR, a co-director of the Oxford-CityU Centre, Hong Kong, a PI at Pandemic Sciences Institute, Oxford, a Visiting Chair in AI for Health at the University of Manchester, and a Fellow of Fudan University, China, an associate editor of IEEE Rev Biomed Eng and IEEE J Biomed Health Inform, etc. He has published over 400 papers with over 26K citations and an H-index of 77, holds over 30 patents, and has incubated over 5 Oxford spin-out companies. He has won over 40 awards, including the Wellcome Trust Discovery Award, IEEE Early Career Award (awarded to one engineer annually), Oxford’s inaugural “Vice-Chancellor’s Innovation Prize”, EPSRC Fellowship for nine “future leaders in healthcare”, etc.牛津大学高等研究院(苏州)招聘医疗人工智能研究员

岗位职责
1. 在计算健康信息学领域提出研究问题,开展个人研究,分析复杂的定性和定量数据,并在现有概念的基础上产生原创想法。2. 开发和建立的合适的分析方法和技术以支持研究。

3. 定期在国际高水平期刊和书籍章节中撰写国际水平的研究文章。在国内和国际会议上发表论文,并主持研讨会以传播研究成果。

4. 制定明确的任务目标,组织工作并与团队成员合作研究,对擅长的方法对团队的其他成员进行指导。

5. 与合作机构开展合作项目。

6. 在实验室环境中使用实验设备,尤其是用于机器学习的计算相关设备。

7. 对项目进行文献检索,并向研究团队和其他感兴趣的各方展示研究结果。

8. 关注对机器学习领域的发展及其在实际中的应用。

Responsibilities
1. Develop research questions within the field of computational health informatics, conduct individual research, analysing detailed and complex qualitative and/or quantitative data from a variety of sources, and generate original ideas by building on existing concepts.2. Develop, establish, and pursue appropriate analytical protocols and techniques to support research.

3. Regularly write research articles at an international level for peer-reviewed journals, book chapters, and reviews. Present papers at national and international conferences, and lead seminars to disseminate research findings.

4. Agree clear task objectives, organise, and delegate work to other members of the team and coach other members of the group on specialist methodologies or procedures.

5. Carry out collaborative projects with colleagues in partner institutions, and research groups.

6. Use scientific equipment in a laboratory environment, especially pertaining to computational systems typically used for machine learning.

7. Undertake literature searches for the project where appropriate, and interpret and present the findings to the research team and other interested parties.

8. Keep informed of developments in the field of machine learning and its application to the problem domain.

选拔标准 Selection criteria
基本条件
1. 具有人工智能、数据处理或相关领域博士学位;2. 在机器学习、信号处理、计算统计学或相关应用领域发表过有影响力的文章;

3. 具有充分的专业知识,能使用机器学习工具分析医疗健康数据,开展研究和方法论工作;

4. 具有可靠的数学能力,掌握Matlab或Python编程数据分析方法。

优先考虑
1. 具有对医疗健康应用领域的兴趣。2. 具备大语言模型与基础模型的研究经验。

Essential
1. Hold a relevant Ph.D/D.Phil in AI, signal processing, or a cognate discipline;2. Strong publication record in machine learning, signal processing, computational statistics, or a cognate application area;

3. Possess specialist knowledge (sufficient to develop research projects and methodologies) in the fields of machine learning tools for analysing healthcare data;

4. Proven competence in mathematics and programming data analysis methods in Matlab or Python.

Desirable
1. An interest in the application area of healthcare.2. Experience in large language model and foundation models research.

如何申请 How to apply
请将你的求职申请发送到HR@oxford-oscar.cn1. 电子邮件的标题是姓名+应聘岗位。

2. 邮件请附上一份中英文双语求职信和简历。

Please submit a covering letter and CV (in both English and Chinese) by email attachment to HR@oxford-oscar.cn.Email subject: your name and the title of the post for which you are applying.

 

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