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Title: Statistical mentoring at early training and career stages

Abstract

At Los Alamos National Laboratory (LANL), statistical scientists develop solutions for a variety of national security challenges through scientific excellence, typically as members of interdisciplinary teams. At LANL, mentoring is actively encouraged and practiced to develop statistical skills and positive career-building behaviors. Mentoring activities targeted at different career phases from student to junior staff are an important catalyst for both short and long term career development. This article discusses mentoring strategies for undergraduate and graduate students through internships as well as for postdoctoral research associates and junior staff. Topics addressed include project selection, progress, and outcome; intellectual and social activities that complement the student internship experience; key skills/knowledge not typically obtained in academic training; and the impact of such internships on students’ careers. Experiences and strategies from a number of successful mentorships are presented. Feedback from former mentees obtained via a questionnaire is incorporated. As a result, these responses address some of the benefits the respondents received from mentoring, helpful contributions and advice from their mentors, key skills learned, and how mentoring impacted their later careers.

Authors:
 [1];  [1];  [1];  [1]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOD; USDOE
OSTI Identifier:
1312573
Report Number(s):
LA-UR-15-29115
Journal ID: ISSN 0003-1305
Grant/Contract Number:
AC52-06NA25396
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
American Statistician
Additional Journal Information:
Journal Name: American Statistician; Journal ID: ISSN 0003-1305
Publisher:
Taylor & Francis
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; applied research; applications; career; interpersonal skills; networking; presenting; publishing; science; service; technical skills

Citation Formats

Anderson-Cook, Christine M., Hamada, Michael S., Moore, Leslie M., and Wendelberger, Joanne R. Statistical mentoring at early training and career stages. United States: N. p., 2016. Web. doi:10.1080/00031305.2016.1200491.
Anderson-Cook, Christine M., Hamada, Michael S., Moore, Leslie M., & Wendelberger, Joanne R. Statistical mentoring at early training and career stages. United States. doi:10.1080/00031305.2016.1200491.
Anderson-Cook, Christine M., Hamada, Michael S., Moore, Leslie M., and Wendelberger, Joanne R. 2016. "Statistical mentoring at early training and career stages". United States. doi:10.1080/00031305.2016.1200491. https://www.osti.gov/servlets/purl/1312573.
@article{osti_1312573,
title = {Statistical mentoring at early training and career stages},
author = {Anderson-Cook, Christine M. and Hamada, Michael S. and Moore, Leslie M. and Wendelberger, Joanne R.},
abstractNote = {At Los Alamos National Laboratory (LANL), statistical scientists develop solutions for a variety of national security challenges through scientific excellence, typically as members of interdisciplinary teams. At LANL, mentoring is actively encouraged and practiced to develop statistical skills and positive career-building behaviors. Mentoring activities targeted at different career phases from student to junior staff are an important catalyst for both short and long term career development. This article discusses mentoring strategies for undergraduate and graduate students through internships as well as for postdoctoral research associates and junior staff. Topics addressed include project selection, progress, and outcome; intellectual and social activities that complement the student internship experience; key skills/knowledge not typically obtained in academic training; and the impact of such internships on students’ careers. Experiences and strategies from a number of successful mentorships are presented. Feedback from former mentees obtained via a questionnaire is incorporated. As a result, these responses address some of the benefits the respondents received from mentoring, helpful contributions and advice from their mentors, key skills learned, and how mentoring impacted their later careers.},
doi = {10.1080/00031305.2016.1200491},
journal = {American Statistician},
number = ,
volume = ,
place = {United States},
year = 2016,
month = 6
}

Journal Article:
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  • Here, we propose a relationship between the dynamics in the amorphous and crystalline domains during polymer crystallization: the fluctuations of ordering-rate about a material-specific value in the amorphous phase drive those fluctuations associated with the increase in percent crystallinity. This suggests a differential equation that satisfies the three experimentally observed time regimes for the rate of crystal growth. To test this postulated expression, we applied a suite of statistical learning tools to molecular dynamics simulations to extract the relevant phenomenology. This study shows that the proposed relationship holds in the early time regime. It illustrates the effectiveness of soft computingmore » tools in the analysis of coarse-grained simulations in which patterns exist, but may not easily yield to strict quantitative evaluation. This ability assists us in characterizing the critical early time molecular arrangement during the primary nucleation phase of polymer melt crystallization. In addition to supporting the validity of the proposed kinetics expression, the simulations show that (i) the classical nucleation and growth mechanism is active in the early stages of ordering; (ii) the number of nuclei and their masses grow linearly during this early time regime; and (iii) a fixed inter-nuclei distance is established.« less