全球一體化對人類健康提出了前所未有的挑戰(zhàn)，迫切需要培養(yǎng)和造就具國際水平和綜合能力的新一代領(lǐng)軍人才,針對關(guān)鍵的瓶頸問題，開展創(chuàng)新研究、改革創(chuàng)新體制，全面提升創(chuàng)新能力。生命醫(yī)學(xué)領(lǐng)域的創(chuàng)新發(fā)展，臨床研究和監(jiān)管審批是兩大重要環(huán)節(jié)，共同肩負(fù)著對候選藥物和醫(yī)療器械安全性和有效性的科學(xué)評估，是龐大和復(fù)雜的系統(tǒng)工程，是推動創(chuàng)新成果轉(zhuǎn)化的根本保障。為此，清華大學(xué)醫(yī)學(xué)院與葛蘭素史克合作，共同培養(yǎng)清華大學(xué)“臨床研究”、“監(jiān)管科學(xué)”與“人工智能”博士后。希望有志的學(xué)生們踴躍報(bào)名，開拓視野，提高能力，展示才華，為“健康中國”和世界人民的健康福祉做突出貢獻(xiàn)。博士后研究目標(biāo)和遴選要求如下：

1.臨床研究博士后項(xiàng)目

1.1培養(yǎng)目標(biāo)：臨床研究博士后項(xiàng)目著重培養(yǎng)醫(yī)學(xué)畢業(yè)生的新藥設(shè)計(jì)與研發(fā)能力，深入?yún)⑴cGSK的藥品臨床試驗(yàn)流程，熟練掌握藥物分析中生物統(tǒng)計(jì)學(xué)的應(yīng)用，藥代動力學(xué)評估的原理及方法等。

1.2職位要求：

·獲藥學(xué)，醫(yī)學(xué)，或理學(xué)博士學(xué)位

·熟練掌握英語

·符合清華大學(xué)博士后入站要求

1.3培養(yǎng)活動：

·協(xié)助GSK臨床科學(xué)家的新藥在研項(xiàng)目

·在GSK的不同部門進(jìn)行輪轉(zhuǎn)，了解新藥研發(fā)的整體流程

·學(xué)習(xí)藥物動力學(xué)以及生物統(tǒng)計(jì)學(xué)等在新藥評估中的應(yīng)用方法

·豐富的學(xué)術(shù)討論與交流活動

1.4培養(yǎng)目標(biāo)：

·了解臨床研究在新藥研發(fā)中的重要性

·掌握臨床數(shù)據(jù)分析的原理與方法

·熟悉藥物分析的先進(jìn)技術(shù)與局限性

·理解特殊群體臨床試驗(yàn)中應(yīng)設(shè)計(jì)的要素

·完成項(xiàng)目總結(jié)報(bào)告

2.監(jiān)管科學(xué)博士后項(xiàng)目

2.1培養(yǎng)目標(biāo)：監(jiān)管科學(xué)博士后將與GSK的藥品監(jiān)管部門以及傳染病與公共健康研究中心的工作人員一起為GSK的臨床新藥項(xiàng)目提供監(jiān)管科學(xué)支持。

2.2職位要求：

·獲藥學(xué)，醫(yī)學(xué)，或理學(xué)博士學(xué)位

·熟練掌握英語

·符合清華大學(xué)博士后入站要求

2.3培養(yǎng)活動：

·了解中國藥品審批指導(dǎo)原則與政策

·掌握藥品研發(fā)與評估的原理及應(yīng)用

·熟悉藥品IND，NDA申請的要求與方法

·研究監(jiān)管政策的發(fā)展，應(yīng)用，以及指導(dǎo)原則的解析

3.人工智能/機(jī)器學(xué)習(xí)博士后項(xiàng)目

3.1培養(yǎng)目標(biāo)：人工智能/機(jī)器學(xué)習(xí)博后為初級研究人員提供了一個(gè)良好的機(jī)會，可以在兩年時(shí)間內(nèi)參與AI/ML研究，以應(yīng)對藥物和疫苗研發(fā)中的關(guān)鍵挑戰(zhàn)。博后有機(jī)會參與的這些項(xiàng)目，將提高我們對經(jīng)過基因驗(yàn)證的疾病生物學(xué)對公共衛(wèi)生重要治療領(lǐng)域的理解。該項(xiàng)目除了具備一般博后項(xiàng)目的全部優(yōu)勢以外，還能讓博后有機(jī)會與GSK的人工智能和機(jī)器學(xué)習(xí)小組專家全面接觸。

3.2職位要求：博后選拔將綜合多種因素，包括教育背景、相關(guān)經(jīng)驗(yàn)、職業(yè)發(fā)展目標(biāo)等，另外還需要：

·符合清華大學(xué)博士后入站要求

·獲機(jī)器學(xué)習(xí)，統(tǒng)計(jì)，數(shù)學(xué)，計(jì)算機(jī)科學(xué)，物理學(xué)或相關(guān)定量領(lǐng)域的博士或碩士學(xué)位

·至少精通一種編程語言，例如Python

·能進(jìn)行獨(dú)立研究

·熟練掌握英語

·具有基于機(jī)器學(xué)習(xí)的開發(fā)和應(yīng)用的方法的經(jīng)驗(yàn)，至少一種深度學(xué)習(xí)框架（例如PyTorch，TensorFlow或Keras）的經(jīng)驗(yàn)。

·對人工智能的醫(yī)療/制藥應(yīng)用感興趣

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.

申請方式：

應(yīng)聘者請將個(gè)人中英文簡歷及相關(guān)材料發(fā)送至zhangqi2013@mail.tsinghua.edu.cn。郵件主題請注明應(yīng)聘清華大學(xué)“臨床研究”、“監(jiān)管科學(xué)”與“人工智能”博士后 ，簡歷文件名稱請包含姓名。申請截止日期2022年02月28日。

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.

信息來源于網(wǎng)絡(luò)，如有變更請以原發(fā)布者為準(zhǔn)。

來源鏈接：

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

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