NRT-DESE: Training in Data-Driven Discovery - From the Earth and the Universe to the Successful Careers of the Future

NRT-DESE:数据驱动发现培训 - 从地球和宇宙到未来成功的职业生涯

基本信息

  • 批准号:
    1450006
  • 负责人:
  • 金额:
    $ 296.66万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2015
  • 资助国家:
    美国
  • 起止时间:
    2015-04-01 至 2021-08-31
  • 项目状态:
    已结题

项目摘要

This National Science Foundation Research Traineeship (NRT) award prepares master's and doctoral students at Northwestern University with the data-analysis skills to advance the research frontiers in astronomy, physics, and Earth science. While providing students with training in data-enabled science and engineering, the program promotes collaborations with research and education that will lead to the development of new data tools with broad applicability. Through internships, evidence-based curricular approaches, and capstone citizen science projects, trainees will develop the core competencies in demand by a wide range of employers. Trainees will learn how to effectively engage the public in discoveries on the solar system, stellar explosions, star clusters and galaxies, gravitational waves, and seismic waves. The citizen science projects will be used for innovative recruiting, strengthening the participation of the public and students from underrepresented groups. By diversifying the graduate student population and improving instruction and mentoring, the research will be contributing to a diverse, inclusive scientific workforce in academia and industry.This program will bridge computer science, electrical engineering, applied math, and statistics to physics, astronomy, and Earth sciences in order to develop students with the skills required to analyze datasets of unprecedented size and complexity. Trainees will be prepared for the technical challenges of extensive data generated at major research equipment and facilities, including Large Syntopic Survey Telescope, Advanced Laser Interferometer Gravitational-wave Observatory, and EarthScope. Trainees will learn data analytics and management, statistical methods, and image processing skills to ask new questions and choose the appropriate tools from the method disciplines and adapt them to solve problems in physics, astronomy, and Earth sciences. The program will also prepare students to work in a collaborative scientific community, advancing their leadership, communication, mentoring, and management skills. Internships at major research facilities, national laboratories, and the private sector will help students gain transferrable professional skills to pursue a range of career paths.
这一国家科学基金会研究培训(NRT)奖为西北大学的硕士和博士生培养数据分析技能,以推进天文学、物理学和地球科学的研究前沿。在为学生提供数据使能的科学和工程方面的培训的同时,该项目促进了与研究和教育的合作,这将导致开发具有广泛适用性的新数据工具。通过实习、以证据为基础的课程方法和最重要的公民科学项目,受训人员将发展广泛雇主所需的核心能力。学员将学习如何有效地让公众参与太阳系、恒星爆炸、星团和星系、引力波和地震波的发现。公民科学项目将用于创新招聘,加强公众和代表不足群体的学生的参与。通过使研究生群体多样化,并改善教学和指导,这项研究将为学术界和工业界建立一支多样化、包容性的科学队伍做出贡献。该项目将把计算机科学、电气工程、应用数学和统计学与物理、天文学和地球科学联系起来,以培养学生分析前所未有的规模和复杂性的数据集所需的技能。学员将为主要研究设备和设施产生的大量数据的技术挑战做好准备,这些设备和设施包括大型同步测量望远镜、先进激光干涉仪引力波天文台和地球望远镜。学员将学习数据分析和管理、统计方法和图像处理技能,以提出新的问题,并从方法学科中选择合适的工具,并使其适用于解决物理、天文学和地球科学中的问题。该计划还将为学生在合作的科学社区中工作做好准备,提高他们的领导力、沟通、指导和管理技能。在主要研究机构、国家实验室和私营部门的实习将帮助学生获得可转移的专业技能,以追求一系列职业道路。

项目成果

期刊论文数量(0)
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会议论文数量(0)
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Vassiliki Kalogera其他文献

X-Ray Binaries in Nearby Galaxies
  • DOI:
    10.1007/s10509-006-9125-9
  • 发表时间:
    2006-07-21
  • 期刊:
  • 影响因子:
    1.500
  • 作者:
    Vassiliki Kalogera
  • 通讯作者:
    Vassiliki Kalogera

Vassiliki Kalogera的其他文献

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{{ truncateString('Vassiliki Kalogera', 18)}}的其他基金

Gravitational-Wave Data Analysis and Population Inference
引力波数据分析和总体推断
  • 批准号:
    2207945
  • 财政年份:
    2022
  • 资助金额:
    $ 296.66万
  • 项目类别:
    Standard Grant
Gravitational-Wave Inference from Binary Compact Objects
二元致密天体的引力波推断
  • 批准号:
    1912648
  • 财政年份:
    2019
  • 资助金额:
    $ 296.66万
  • 项目类别:
    Standard Grant
MRI: Acquisition of a High-Performance Computing Cluster to Unveil the Sources of Gravitational Waves
MRI:购买高性能计算集群来揭示引力波的来源
  • 批准号:
    1726951
  • 财政年份:
    2017
  • 资助金额:
    $ 296.66万
  • 项目类别:
    Standard Grant
Gravitational-Wave Inference from Binary Compact Objects
二元致密天体的引力波推断
  • 批准号:
    1607709
  • 财政年份:
    2016
  • 资助金额:
    $ 296.66万
  • 项目类别:
    Continuing Grant
INSPIRE: Teaming Citizen Science with Machine Learning to Deepen LIGO's View of the Cosmos
INSPIRE:将公民科学与机器学习相结合,深化 LIGO 的宇宙观
  • 批准号:
    1547880
  • 财政年份:
    2015
  • 资助金额:
    $ 296.66万
  • 项目类别:
    Continuing Grant
Supernova Progenitors, Stellar Remnants, and their Binary Companions
超新星前身、恒星遗迹及其双星伴星
  • 批准号:
    1517753
  • 财政年份:
    2015
  • 资助金额:
    $ 296.66万
  • 项目类别:
    Standard Grant
REU Site: Preparing a Diverse Workforce through Interdisciplinary Astrophysics Research
REU 网站:通过跨学科天体物理学研究培养多元化的劳动力
  • 批准号:
    1359462
  • 财政年份:
    2014
  • 资助金额:
    $ 296.66万
  • 项目类别:
    Continuing Grant
Gravitational-Wave Astrophysics: Getting Ready for the Advanced LIGO Era
引力波天体物理学:为高级 LIGO 时代做好准备
  • 批准号:
    1307020
  • 财政年份:
    2013
  • 资助金额:
    $ 296.66万
  • 项目类别:
    Continuing Grant
MRI: Acquisition of A Hyrid High Performance Computer Cluster for Gravitational-Wave Source Simulation and Data Analysis
MRI:获取用于引力波源模拟和数据分析的混合高性能计算机集群
  • 批准号:
    1126812
  • 财政年份:
    2011
  • 资助金额:
    $ 296.66万
  • 项目类别:
    Standard Grant
GRAVITATIONAL-WAVE ASTRONOMY WITH BINARY COMPACT OBJECTS: SOURCE MODELING AND LIGO DATA ANALYSIS
双致密天体的引力波天文学:源建模和 LIGO 数据分析
  • 批准号:
    0969820
  • 财政年份:
    2010
  • 资助金额:
    $ 296.66万
  • 项目类别:
    Standard Grant

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  • 批准号:
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