The SONIC research group and ATLAS laboratory at Northwestern University invite applications for a research lab manager to support lab directors Noshir Contractor (SONIC) and Leslie DeChurch (ATLAS) on administrative and operational aspects of their research portfolios here at Northwestern University – Evanston Campus.

The lab manager will be responsible for supporting a variety of lab operations, including reporting and compliance requirements, communication of findings through digital displays and online materials, and organization and updating of research materials and files. In addition, the lab manager will assist in training new lab members and other research related activities.

Responsibilities:

• Preparation and submission of grant reports and other administrative documents needed for compliance.
• Preparation of materials to promote our research on digital displays and lab websites.
• Regularly update lab databases tracking publications, presentations, personnel, and other information needed for laboratory operations.
• Oversee IRB procedures and maintain confidentiality of participant information; ensures compliance with institutional, state and federal regulatory policies, procedures, directives and mandates.
• Miscellaneous laboratory management tasks such as ordering supplies and maintaining equipment.

Required Competencies:

• Strong project management skills with exceptional attention to detail.
• Excellent written and verbal communication skills.
• Outstanding interpersonal skills and ability to maintain positive relationships with various stakeholders.
• Strong time management skills with a proven ability to multitask and to prioritize activities to successfully complete projects on tight deadlines with little supervision.
• Knowledge of Microsoft Office, Dropbox, and Google Drive required.
• Willingness to learn scientific formatting requirements (e.g., APA format) in preparing research materials.
• Ability to work independently and as part of a team.

Education and Experience:

• Bachelor’s degree required, preferably in Communication, Psychology, Sociology, Business, Industrial Engineering, or a social science field.
• Experience in an interdisciplinary research environment preferred.
• Experience with IRB or grant-writing preferred.

Applicants should send a cover letter, resume, and three references (i.e., contact details) to Brent Hoagland (brent.hoagland@northwestern.edu). Additionally, Northwestern University will have a formal application process.

To bring the performance of people analytics up—and in line with the hype— organizations need to do more than analyze data on demographic attributes.  They need to employ relational analytics, which examines data on how people interact, to identify “high potentials,” who has good ideas, who is influential, what teams will get work done on time, and more. Companies can mine their “digital exhaust”—data created by employees every day in their digital transactions, such as e‐mails, chats, “likes,” “follows,” @mentions, and file collaboration—for insights into their workforce. Drawing from our ongoing research on space missions, as well as from a large body of other scholars’ research, we identify structural signatures to help organizations address challenges they face with issues such as team conflict, team assembly, diversity and inclusion, succession planning, team assembly, and post-merger integration.

Website: https://www.networkscienceinstitute.org/events/noshir-contractor

Citation: Contractor, N. (2019, April). People Analytics: Understanding and Enabling the Future of Work. Speaker at Northeastern University’s Network Science Institute, Boston, MA.

Citation: Contractor, N. (2019, March). Leveraging the Next Decade of Computational Social Science to Address Grand Societal Challenges. Speaker at University of Michigan’s Survey Research Center (SRC) Seminar Series, Ann Arbor, MI.

Professor Contractor presented, “Using optimization methods to benchmark performance in space teams” at Management Science Workshop 2019 in Santa Cruz, Chile.

The presentation was about providing a performance measurement method based on optimization techniques for Multi-Team Systems (MTS). The method is tested on an MTS for Project RED -a project funded by the National Aeronautics and Space Administration (NASA). The main goal of the MTS is planning the development of a water well to support a human colony on Mars.

This workshop is sponsored by the Department of Industrial Engineering, Universidad de Chile and Complex Engineering Systems Institute. The workshop was successful in bringing together researchers and innovators from many leading universities and business schools such as MIT, Management Sloan School, U.C Berkeley, Northwestern, Yale University, etc. to connect, meet and establish channels for collaboration.

Citation: Izadinia, N., DeChurch, L., Contractor, N., & Waechter, A. (2019, January). Introducing a measure for calculating the efficiency of work in space. Paper presented at 2019 Management Science Workshop, Santa Cruz, Chile.

Acknowledgment: This research is funded by the National Aeronautics and Space Administration (NASA), Award number NNX15AK73G

The SONIC Speaker Series presents

George G. Vega Yon

Department of Preventive Medicine at USC’s Keck School of Medicine

Big Problems for Small Networks: Statistical Analysis of Small Networks and Team Performance

SONIC Lab is proud to welcome George G. Vega Yon of USC’s Keck School of Medicine. George will speak on Wednesday, March 20th, 2019 at 2PM in Frances Searle Building, Room 1-483 with a workshop to follow. Please contact Brent Hoagland with any questions.

Abstract:

Small network data such as team, family, or personal networks, is common in many fields that study social networks. Although the analysis of small networks may appear simplistic relative to the difficulties posed by “big” datasets, there are at least two key challenges: (1) fitting statistical models to explain the network structure in small groups, and (2) testing if structural properties of small networks are associated with group-level outcomes; for example, team performance. In this presentation, we introduce two new statistical methods that use a revisited version of Exponential Random Graph Models (ERGMs) in the context of small networks. Using exhaustive enumeration of networks in the support, we are able to calculate exact likelihood functions for ERGMs, which allows us to obtain maximum likelihood estimates directly (without using simulations), avoiding common problems that arise from methods that rely on approximations instead. This is joint work with Prof. Kayla de la Haye (USC).

A workshop on the R packages ergmito and gnet for applying the methods introduced during the talk will be conducted.