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清华大学医学院2022年1月招聘“临床研究”、“监管科学”与“人工智能”博士后
文章来源:知识人网整理       更新时间:2022年01月25日

发布时间:2022-01-24

截止日期:2022年2月28日

工作地点:北京

招聘人数:若干

报名方式:电子邮件

需求学科(供参考)

全球一体化对人类健康提出了前所未有的挑战,迫切需要培养和造就具国际水平和综合能力的新一代领军人才,针对关键的瓶颈问题,开展创新研究、改革创新体制,全面提升创新能力。生命医学领域的创新发展,临床研究和监管审批是两大重要环节,共同肩负着对候选药物和医疗器械安全性和有效性的科学评估,是庞大和复杂的系统工程,是推动创新成果转化的根本保障。为此,清华大学医学院与葛兰素史克合作,共同培养清华大学“临床研究”、“监管科学”与“人工智能”博士后。希望有志的学生们踊跃报名,开拓视野,提高能力,展示才华,为“健康中国”和世界人民的健康福祉做突出贡献。博士后研究目标和遴选要求如下:

1.临床研究博士后项目

1.1培养目标:临床研究博士后项目着重培养医学毕业生的新药设计与研发能力,深入参与GSK的药品临床试验流程,熟练掌握药物分析中生物统计学的应用,药代动力学评估的原理及方法等。

1.2职位要求:

·获药学,医学,或理学博士学位

·熟练掌握英语

·符合清华大学博士后入站要求

1.3培养活动:

·协助GSK临床科学家的新药在研项目

·在GSK的不同部门进行轮转,了解新药研发的整体流程

·学习药物动力学以及生物统计学等在新药评估中的应用方法

·丰富的学术讨论与交流活动

1.4培养目标:

·了解临床研究在新药研发中的重要性

·掌握临床数据分析的原理与方法

·熟悉药物分析的先进技术与局限性

·理解特殊群体临床试验中应设计的要素

·完成项目总结报告

2.监管科学博士后项目

2.1培养目标:监管科学博士后将与GSK的药品监管部门以及传染病与公共健康研究中心的工作人员一起为GSK的临床新药项目提供监管科学支持。

2.2职位要求:

·获药学,医学,或理学博士学位

·熟练掌握英语

·符合清华大学博士后入站要求

2.3培养活动:

·了解中国药品审批指导原则与政策

·掌握药品研发与评估的原理及应用

·熟悉药品IND,NDA申请的要求与方法

·研究监管政策的发展,应用,以及指导原则的解析

3.人工智能/机器学习博士后项目

3.1培养目标:人工智能/机器学习博后为初级研究人员提供了一个良好的机会,可以在两年时间内参与AI/ML研究,以应对药物和疫苗研发中的关键挑战。博后有机会参与的这些项目,将提高我们对经过基因验证的疾病生物学对公共卫生重要治疗领域的理解。该项目除了具备一般博后项目的全部优势以外,还能让博后有机会与GSK的人工智能和机器学习小组专家全面接触。

3.2职位要求:博后选拔将综合多种因素,包括教育背景、相关经验、职业发展目标等,另外还需要:

·符合清华大学博士后入站要求

·获机器学习,统计,数学,计算机科学,物理学或相关定量领域的博士或硕士学位

·至少精通一种编程语言,例如Python

·能进行独立研究

·熟练掌握英语

·具有基于机器学习的开发和应用的方法的经验,至少一种深度学习框架(例如PyTorch,TensorFlow或Keras)的经验。

·对人工智能的医疗/制药应用感兴趣

Global integration poses unprecedented challenges to human health, and there is an urgent need to train and produce a new generation of leaders with international standards and comprehensive capabilities, to carry out innovative research, reform innovation systems and comprehensively enhance innovation capabilities in response to key bottlenecks. Innovation and development in the field of life medicine, clinical research and regulatory approval are two important links, shouldering the scientific assessment of the safety and importance of candidate drugs and medical devices, is a huge and complex system engineering, is the fundamental guarantee to promote the transformation of innovation results. To this end, Tsinghua University School of Medicine, in collaboration with GlaxoSmithKline, has trained postdoctoral students in "clinical research" and "regulatory science" and “artificial intelligence/machine learning (AI/ML)”at Tsinghua University. It is hoped that aspiring students will sign up, broaden their horizons, improve their abilities and display their talents, and make outstanding contributions to the health and well-being of "Healthy China" and the people of the world. The postdoctoral research objectives and selection requirements are as follows:

Track 1: Clinical Fellowship

Overall Goal: The Clinical Development Fellowship program is a post graduate research program with a strong emphasis on training and developing the successful Tsinghua medical school graduates who are selected to participate. The Fellows will assist GSK clinical scientists on clinical development programs of GSK compounds. They will receive all necessary GSK trainings and be assigned individual projects under the close supervision of GSK staff. The overall objective of the program is to provide post-graduate practical training or equivalent in the principles and applications of pharmaceutical product development and evaluation; research design and methodology, including development of research protocols in the clinical investigation of new drugs; and principles and applications of biostatistics, advanced pharmacokinetics, laboratory drug analysis, and study design methodology.

Track 2: Regulatory Fellowship

Overall Goal: The goal of this fellowship is to provide on-the-job practical training and experience in key regulatory functions in order to gain expertise in the regulatory requirements of drug development. The fellowship program is a post-graduate training program with a strong emphasis on attracting talents and developing successful Tsinghua candidates who are selected to participate. The Fellows will work with members of the GSK China Regulatory Department and GSK’s Institute for Infectious diseases and public health (IIDPH) to provide regulatory support for clinical development and other GSK programs. Overall this program should enhance the knowledge and real world experience of the fellow and develop a regulatory practitioner prepared for the pharmaceutical industry or academia once the fellowship is completed.

Criteria for selection of Fellows: Fellows will be selected based on education, relevant experience, and career objectives, as well as rules and regulations set forth by the Tsinghua University for postdoctoral fellows. A post graduate degree in PharmD, MD or PhD and Fluency in Englishare required.

Track 3: Artificial Intelligence/Machine Learning Fellowship

Overall Goal: The GSK.ai Fellowship Program offers early-careers researchers the chance to spend two years engaged in AI/ML research applied to key challenges in drug and vaccine discovery and development. Fellows will work on projects to improve our understanding of genetically validated, disease biology for therapy areas of public health importance. The role has all the advantages of an academic posdoctoral position but with the additional benefit of having full access to GSK's artificial intelligence and machine learning group experts.

Criteria for selection of Fellows: Fellows will be selected based on education, relevant experience, and career objectives, as well as rules and regulations set forth by the Tsinghua University for postdoctoral fellows. Candidates must have a post graduate degree PhD or Masters in machine learning, statistics, mathematics, computer science, physics or a related quantitative field. Expert understanding of at least one programming language such as Python. Experience of carrying out independent research and Fluency in English. Ideal candidates will also have experience of developing and applying machine learning-based methodologies and at least one deep learning framework such as PyTorch, TensorFlow or Keras.Desirable: an interest in medical /pharma applications of ai.

申请方式:

应聘者请将个人中英文简历及相关材料发送至zhangqi2013@mail.tsinghua.edu.cn。邮件主题请注明应聘清华大学临床研究监管科学人工智能博士后,简历文件名称请包含姓名。申请截止日期20220228

How to apply:

Candidates are requested to send their resumes and related materials to zhangqi2013@mail.tsinghua.edu.cn. Please indicate the subject of the email to apply for Tsinghua University "clinical research" and "regulatory science" and “artificial intelligence/machine learning” postdoctoral. Application deadline: Feb 28, 2021.

信息来源于网络,如有变更请以原发布者为准。

来源链接:

https://www.med.tsinghua.edu.cn/info/1374/3890.htm

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