News

Professor Intisar Rabb and data science fellow Dr Yusuf Celik at the Program in Islamic Law / SHARIAsource Lab at Harvard Law School are looking for research assistants with a computer science / machine learning background this fall for a digital humanities project. 

Are you interested in applying Machine Learning to texts? Curious to see a Digital Humanities project in action? Well, look no further! At Harvard’s Program in Islamic Law we are currently looking for 1-2 research assistants in Digital Humanities that can help with the implementation of Machine Learning techniques within the Courts and Canons project. As an assistant in the Digital Humanities you are expected to participate in one of the ongoing Machine Learning endeavors, such as the implementation of Named Entity Recognition or topic modeling. Expected is an intermediate knowledge of Python, Arabic, and conceptual grasp of various Machine Learning concepts (e.g. Neural Networks, Deep Learning, etc.). Having experience in one of the known Machine Learning frameworks is a plus (e.g. PyTorch, TensorFlow, etc.). Assistants will be expected to report on their progress on a weekly basis and perform a biweekly demonstration to the entire lab. Lab sessions will meet every other Monday, beginning on September 13th. 

DEADLINE: September 12, by midnight (EST).

TO APPLY: Please send a CV/resume, school transcript, and a brief statement of interest. Submit applications through Formstack.

For questions, contact Abtsam Saleh  at [email protected].

Islamic Law, Data Science, and AI Lab | Spring 2021 | Harvard Law School

Convened by Intisar Rabb & Zahra Takhshid, Harvard Law School 

The PIL Islamic Law Lab seeks applicants interested in presenting or developing works in progress at the intersection of Islamic law and data science for the Spring 2021 Lab, with respect to their own research or to ongoing projects within our Lab. Specifically, our Lab will focus on emerging tools in the Islamic digital humanities / data science space, and to developing new components of our in-house data science tools: Courts & Canons: (1) creating historical gazetteers for the Islamic world, (2) ‘hacking the library’ to make bibliographic library searches in our field more useable and precise, and (3) better understanding and mapping Islamic legal genres. This Lab is also launching a research project on “AI Principles in Islam,” by which we aim to assess and develop ethical and legal guidelines that arise in AI from Islamic perspectives. Generally, research themes for which we seek proposals include research queries on Islamic law that make use of a data science/digital humanities tool, method, or a data set to answer novel questions in the fields of Islamic law or history; or algorithms, digital corpora, and other DH / data science tools (e.g., KITAB-project.org, e-Shia.ir, or others). We are open to a diverse set of research inquiries within these specific or general areas. Public lab sessions presenting research will last for one hour, consisting of a 15-20 presentation and 40-45 minutes Q&A. Additional lab lessons (by invitation) will be devoted to building tools native the Lab. We hope the Lab will facilitate students and collaborating scholars to produce publishable papers and data science tools over the course of the Spring semester. Selected work may be considered for publication opportunities on the Islamic Law Blog or the Journal of Islamic Law (research), and the SHARIAsource portal (tools).

TO APPLY: Lab sessions will meet on the following dates, with 3 public sessions (for research) and 3 closed sessions (for project development): Feb. 1 (introductory meeting), 2/8, 2/22, 3/8, 3/22, 4/5, and 4/19. For interested students, please send a CV and statement of interest and background of no more than one paragraph (including reference to one of the specific listed above). For interested researchers: The deadline to submit your abstract or project proposal is February 5, 2021. Interested candidates should send a CV, abstract for a research paper (of no more than 800 words), and/or links to a website with an abstract representing your work. Submit applications through Formstack. For questions, contact Zahra Takhshid <[email protected]>.