Work with us!

We are currently soliciting applications for a one-year full-time post-doctoral fellowship with expertise in computational and network social science on the topic related to gender and collaboration.  

Please see further details below and feel free to forward this to any contacts.

Apply online through the SCU job portal.

Postdoctoral Fellow in Network Science

Location:  Santa Clara University (Santa Clara, CA) with potential for remote work in CA, OR, WA, IL, AZ, NV

PURPOSE:

This is a one-year (non-tenure-track) postdoctoral research opportunity working at Santa Clara University, a Jesuit, Catholic university. There is no requirement that staff, faculty, or students declare membership in the Catholic religion. The successful candidate will work with co-PIs King, Whittington, and Frederickson on projects related to the NSF-funded grant project “Gender Differences in Co-authorship across a Global Landscape.” The position will focus on analysis of massive bibliometrics data, looking at collaborations among authors in a database of scientific publications.  In addition to collaborating on data analysis and publication writing, the postdoc will also have the opportunity to mentor talented undergraduates in advancing the research project. Please see this page more information about the project and co-PIs. 

HIRING RANGE:

Full-time position includes: 

• Eligible for employment benefits and health insurance

• Academic and professional development opportunities

• Travel funds for visits with study co-PIs, attending conferences and workshops

• Salary of $68,000

BASIC QUALIFICATIONS: 

Candidates for this position should have:

1. A Ph.D. in a relevant field. We are open to candidates with social science backgrounds (e.g., sociology, history and philosophy of science, science & technology studies, computational social science) and/or computational science backgrounds (e.g., statistics, information science, cognitive science, computer science, applied mathematics, physics, network science). The candidate must complete their Ph.D. prior to the commencement of this position, and must have completed their Ph.D. less than 5 years prior.

2. Expertise in techniques relevant to computational social science and network analysis.  While candidates need not have experience studying scientists, scientific publications, and other traces of scientific activity, such background is certainly desirable.  Candidates should have experience with social science applications and methodological approaches, including statistical techniques for multivariate analysis and/or social network analysis.

3. Excellent programming skills in R and or/ Python (required), familiarity with network programming packages (preferred), and/or Stata (preferred).

4. A good command of spoken and written English.

Santa Clara University is committed to the strategic goal of enriching the quality of our community of scholars by increasing diversity among faculty, staff, and students. Candidates who can contribute to this goal are encouraged to apply and to identify their strengths or experiences related to achieving this goal in their letter of application.

PREFERRED QUALIFICATIONS:

1. Familiarity with citation analysis, including the collection of data from bibliometric sources, assessment of collaborative patterns and dynamics, use of large-scale datasets for the construction of citation statistics (i.e. Scopus, Web of Science, etc), and knowledge of and familiarity with the use of backward and forward citation statistics.

2. Candidates with familiarity in: network science, complex systems, statistical modeling, and/or computational social science. Candidates whose research contributes to, or with demonstrated interest in, one of more of the following areas:

   1. Network theory and methodology

   2. Dynamics of networks

   3. Science of science

   4. Gender and Scientific Work

3. Experience with exploratory data analysis: feature extraction, visualization, etc.

4. Experience using social science data in a multivariate framework, and with social network analysis.

5. An interest in focusing efforts on the topic of gender equity in science, with a strong emphasis on the application of social theories of stratification to quantitative data on gender and collaborative activity.

6. Demonstrated excellence in academic research via peer-reviewed publications.

7. Experience and/or demonstrated interest in working with undergraduate students on research projects.

RESPONSIBILITIES:

1. Research and Analysis: Conduct data analysis of large-scale bibliometrics data. Deploy social network analysis and multivariate statistics to study men’s and women’s collaborative positioning in global co-authorship networks over time.

2. Dissemination and Publication: Collaborate with the research team to publish research findings in reputable academic journals and present research outcomes at conferences and on campus.

3. Mentorship and Collaboration: Actively engage in mentoring undergraduate students, providing guidance and support on the project. Foster collaborative relationships with co-PIs.

4. Grant Reporting: Contribute to the preparation of the annual grant progress report and outcomes.

5. Project Coordination: Help coordinate research projects within the computational social science research group. This includes managing project timelines, setting intermediate milestones, and overseeing the work of undergraduate research assistants or team members. 

Note: The responsibilities listed above are indicative and may be adapted to suit the specific needs and priorities of the research project and team.

HOW TO APPLY:

All applications should submit the following to the online job application portal for Santa Clara University:

1. a cover letter with a brief description of interest in joining this project and how it could foster your professional development and career trajectory, and how your interests fit those of our research group on gender inequalities and collaboration;

2. a CV 

3. a brief research statement (2 pages) of previous experience with social research, ongoing, and future research plans, especially as they apply to the focus of this project and your interests.  Please describe your technical skills, areas of expertise, and the type of advanced training that you would like to receive as a fellow. Please also describe your experience, if any, mentoring or working with undergraduate students. 

4. examples of at least one writing sample of relevant and/or past work.  

5. the names and contact information for 2 academic references. We will contact recommenders separately after initial application review.  

All qualified applicants will receive full consideration without regard to race, color, sex, gender, sexual orientation, religion, national origin, disability, protected veteran status, or any other basis protected by law. Women, people with disabilities, and underrepresented minority applicants are strongly encouraged to apply.

All qualified applicants will receive full consideration without regard to race, color, sex, gender, sexual orientation, religion, national origin, disability, protected veteran status, or any other basis protected by law. Women, people with disabilities, and underrepresented minority applicants are strongly encouraged to apply.

Review of applications will continue until the position is filled.