BECOME A FULBRIGHT PHD SCHOLAR AT QUEEN’S

Applications for the academic year 2020-21 competition are now closed. Applications will re-open in August 2020.

Ann Browne was born October 18, 1949 in Strabane, Northern Ireland, and died of cancer on January 29, 2000.  She read Spanish at Queen’s University Belfast and graduated in the early 1970s.  She then took an MA at London’s Institute of Latin American Studies, before visiting Latin America.  She was inspired by Latin American Literature and the Northern Ireland civil rights movements.  She fought for the rights of Latin American miners, was a Trade Unionist, and supported Chilean refugees.  She moved to Brussels, where she died in 2000. 

To honour her memory and spirit the Browne family set up the Ann Browne Masters Scholarship in Conflict Transformation and Social Justice to commemorate her life and work.

The LINAS Doctoral Training Programme (DTP) seeks to develop a cohort of Doctoral Scholars who can address the implications of massive-scale data processing, artificial intelligence (AI) and machine learning (ML) for both the actual operation of algorithmically driven public decision-making in wider society, and within science and engineering.

Together the rapidly evolving approaches to data make up what have been termed ‘enigmatic technologies’, where authority is concealed behind algorithms. Within the social science domain, algorithmically driven public decision-making, challenges the role of human agency and politics, human rights law and principles of transparency and accountability. For science and engineering, there is a challenge to the traditional scientific governing principles of transparent working and reproducibility. 

LINAS brings together legal scholars, social scientists, physical scientists, mathematicians, computer scientists and engineers to develop a distinctive cohort of doctoral students working across the boundaries of their own disciplines. Our ambition is to support the development of integrated, effective, scientifically rigorous and socially responsible algorithmic solutions.