D-Lab Data Science Fellows Program

We are excited to announce the launch of the D-Lab Data Science Fellows Program, with the inaugural cohert starting Spring 2019.

 

D-LAB FELLOWS

The D-Lab Data Science Fellows program is designed to give outstanding UC Berkeley students and researchers the opportunity to advance their data science training within the D-Lab’s diverse and intellectually vibrant community.  We offer participants a supportive mentorship and peer-learning environment in which they can apply their expertise and knowledge, gain professional teaching and leadership skills and connect with industry and public sector partners.

D-Lab Data Science Fellowships are awarded to facilitate and recognize significant contributions to one or more core areas in service to the D-Lab community and constituencies.  Fellows can make contributions in one or more of the following areas:

Workshops. D-Lab provides daily workshops on topics including but not limited to: R, Python, and Stata programming, maps and spatial analysis in GIS, survey design in Qualtrics, qualitative data analysis in MaxQDA, data visualization in Tableau, Excel for data analysis, and the latest techniques for text analysis and machine learning in R and Python. Visit our calendar frequently as new workshops are added throughout the semester.

Consulting. D-Lab also offers one-on-one consulting on research design, data analysis, data management, and related techniques and technologies to all members of the campus community free-of-charge. This is a great way to get a second opinion on your research design, insights on a new method, help with a technical tool, or advise about available data. Make an appointment on our consulting page.

Working Groups. D-Lab hosts working groups that allow participants to dive into a topic, develop a community, advance their research interests and work on the cutting edge. While new-comers of any background are always welcome, the working group format works best when participants commit to ongoing collaboration. Returning working groups this Fall include the Computational Text Analysis, Securing Research Data, Power and Learning in Social Media Working Groups.  

Projects. D-Lab also provides learning opportunities to students via research teams, online services, and projects for social good. Examples of these projects include: 

  • Online Learning. We are proud to announce that Sage Publications is partnering with the D-Lab as one of their first data science online course developers and providers of learner support for SAGE Campus. The partnership has yielded a series of modules that introduce applied data science to social scientists. These learning modules demystify the tools and methods of an emerging field that is changing the way we collect, process, and analyze information.
  • Data Science for Social Good. D-Lab researchers are also working hard on real-world problems deploying Data Science for Social Good.  Data Science for Social Good is a meta-organization of the D-Lab that works on issues such as underrepresented minorities in data science, college-going patterns in California, and hate speech.
  • Research Projects. The D-Lab has developed a theoretically informed codebook and hand-labeled hate speech in approximately 9,000 online comments sourced from Reddit in June and July 2015 as well as October and November 2016. We subsequently applied supervised machine learning algorithms to differentiate hate speech from non-hate speech on this labeled text. This project is supported by the Anti-Defamation League, which works in partnership with various platforms.  

Community. What really makes D-Lab special is our community. Students, faculty and staff who use and provide our services, attend our events, and work in our space create a diverse and supportive learning community. Our philosophy is IOKN2K: It's OK Not to Know. We all have learning gaps and can learn from each other. D-Lab seeks to foster a safe, inclusive and respectful space for knowledge sharing.

 

FELLOW EXPECTATIONS

The specifics of Fellow contributions will be determined at the start of the Fellow appointment. However, we expect that Fellows will participate in the D-Lab community via the following activities:

  • serve, in a limited capacity, as a D-Lab consultants,
  • present one workshop or talk per semester,
  • attend a D-Lab working group,
  • participate in research,
  • write at least one D-Lab blog post, and
  • prepare an end of semester report on their activities as a D-Lab Fellow.

 

Fellows will be expected to devote, on average, 5 - 10% of their time on D-Lab research projects and or training activities. This is a limited, yet continuous time commitment, with Fellow involvement at the D-Lab throughout the semester.

 

Eligibility and Application

The D-Lab invites UC Berkeley graduate students, advanced undergraduate students, current postdocs and visiting scholars and staff to apply to the D-Lab Data Science Fellows Program. We welcome applicants from all academic disciplines and methodological approaches. Fellowships are for one year and include recognition of contributions to data science, desk space, and for some campus affiliates, a modest award. Moreover, we offer you a valuable co-working experience alongside campus experts in which you will gain access to professional experiences unparalled on campus.

 

A call for applications for Fall 2019 Fellows will be posted in late Spring 2019. Applicants are encouraged to visit the D-Lab website and attend D-Lab workshops  and working groups as a way to learn more about our services and community.  
 
 

Data Science at the D-Lab

The D-Lab helps Berkeley faculty, staff, and students move forward with world-class research in data-intensive research. We think of data science as an expansive area, one that is constantly changing as the research frontier moves. We offer a venue for methodological exchange from all corners of campus and across its bounds. In one capacity, we provide training and individual consulting on study design, methods and tools such as programming, statistics, machine learning, data collection,  and more. In another capacity, we conduct research on both historical and contemporary issues, with a focus on data science for social good.  Collaborating with other Berkeley institutes, departments and schools, D-Lab services complement and strengthen the breadth and excellence of data science across Berkeley’s academic programs and faculty research. This is exemplified by D-Lab’s close partnerships with the Social Science Matrix, Data Science Education Program, Digital Humanities at Berkeley, the Library, the Berkeley Institute for Data Science, and Research Teaching and Learning.  Since our founding in 2013, we have prioritized keeping D-Lab an inclusive environment that values diversity and open exchange, a culture captured by our motto “It’s OK not to know”.