NLM Research Training Program in Biomedical Informatics and Data Science for Predoctoral and Postdoctoral Fellows

项目总结/摘要 我们寻求更新我们在生物医学信息学和数据科学的NLM研究培训计划 （NLMTP），29年来一直培养出优秀的博士前和博士后学员， 该计划沿着生物医学信息学和数据科学（BMI和DS）本身的发展， 成功地将计算、数据科学、应用数学、统计学、生物医学、建模、数据- 驱动推理和决策，以及认知信息学的进步，对生物医学问题产生影响。 通过这次更新，我们将进一步扩大我们的研究培训计划，以探索和利用动态 BMI和DS与人工智能（AI）的相互作用，包括机器学习，以及它们在 生物医学与人类健康和疾病。我们的计划不仅将装备学员与坚实的DS 方法论和最新的工具，计算方法和统计方法来解决BMI问题， 而且还提供了广泛的基础，使他们能够发明未来的攻击方法， 目前我们无法解决的问题;这将产生新一代的BMI科学家，他们可以提取新的 从经验和实验中获得知识，为基础研究、病人护理和公共卫生提供信息。我们， 因此，寻求培养我们的学生和博士后有效地工作在理论和 实践，知识获取和知识共享之间。我们的46名培训教师，具有广泛的专业知识 在BMI、DS和AI方面，加上基础科学和临床知识，有很高的研究记录。 生产力、广泛的合作和联邦资金。他们的招聘、培训和 包括妇女在内的代表性不足群体的职业发展势头强劲，已辅导了264名 在过去10年中，有208名前博士（31%的UR，39%的女性）和132名博士后 (16% UR，31%女性）目前在实验室。我们的9名博士生将完成一年的学习 在加入NLMTP之前，我加入了六个参与机构之一的实验室（通常为期3年 任命），从而确保他们的研究项目很好地融入NLM的培训领域。我们6 博士后培训生将通过国家招聘和从我们的教师实验室中选择，通常 2-年任命。NLMTP培训将结合联合收割机的BMI和DS核心课程，高级选修课程， 严格性和可重复性的培训以及负责任的研究行为，专业/职业发展 活动，每月与专家举行会议，以及跨学科的双指导研究项目 护理/临床信息学、转化生物信息学和临床研究信息学。我们的研究培训 该计划将由外部专家定期评估，并根据需要进行调整。这个程序 将为学员提供完美的机会，以获得技能，专业知识和智力能力，以培养 创新的研究，并准备他们的应用研究或相关的职业生涯，他们可以深刻 影响个性化医疗、临床决策和数据驱动的健康等关键领域。

PROJECT SUMMARY/ABSTRACT We seek renewal of our NLM Research Training Program in Biomedical Informatics and Data Science (NLMTP), which for 29 years has consistently produced outstanding pre- and postdoctoral trainees as the program has evolved along with Biomedical Informatics and Data Science (BMI and DS) themselves, successfully bringing computation, data science, applied mathematics, statistics, biomedicine, modeling, data- driven inference and decision-making, and advances in cognitive informatics, to bear on biomedical problems. With this renewal, we will further expand our research training program to explore and exploit the dynamic interaction of BMI and DS with artificial intelligence (AI), including machine learning, and their applications in biomedicine and human health and disease. Our program will not only equip trainees with solid DS methodology and the latest tools, computational approaches, and statistical methods to solve BMI problems, but also provide broad foundations that will enable them to invent the methodologies of the future to attack problems currently beyond our reach; this will produce a new generation of BMI scientists who can extract new knowledge from experience and experiment to inform basic research, patient care and public health. We, therefore, seek to train our students and postdocs to work effectively at the interface between theory and practice, between knowledge acquisition and knowledge sharing. Our 46 training faculty, with broad expertise in BMI, DS, and AI coupled with basic science and clinical knowledge, have a record of high research productivity, extensive collaborations, and federal funding. Their track record of the recruitment, training, and career advancement of underrepresented (UR) groups including women is strong, having mentored 264 predocs and 337 postdocs over the past 10 years, with 208 predocs (31% UR, 39% women) and 132 postdocs (16% UR, 31% women) currently in their labs. Our 9 predoctoral trainees will have completed one year of study and joined a lab at one of six participating institutions before joining the NLMTP (typically for 3-year appointments), thus ensuring that their research projects fit well into the training areas of the NLM. Our 6 postdoctoral trainees will be selected through national recruiting and from the labs of our faculty, for typically 2-year appointments. NLMTP training will combine core courses in BMI and DS, advanced elective courses, training in rigor and reproducibility and the responsible conduct of research, professional/career development activities, monthly meetings with experts, and interdisciplinary dual-mentored research projects in health care/clinical informatics, translational bioinformatics, and clinical research informatics. Our research training program will undergo regular evaluations by external experts with adjustments made as needed. This program will provide the perfect opportunity for trainees to acquire the skills, expertise and intellectual abilities to foster innovative research and prepare them for applied research or related careers in which they can profoundly affect such critical areas as personalized medicine, clinical decision making, and data-driven health.