PhD opportunity - Machine learning for program synthesis

Supervisor: Christina David

Summary: Program synthesis tools relieve the programmer from thinking about how the problem is to be solved, allowing them to focus on providing a description of what is to be achieved.

You will be joining a group to work on advancing the state of the art in program synthesis, focusing in particular on integrating new program synthesis techniques such as Counter-Example Guided Inductive Synthesis (CEGIS), with machine learning.

A strong foundation in the principles of programming languages and their semantics is essential, with demonstrable exposure and an interest in machine learning a significant plus. An early start (February or March 2020) is possible depending on the candidate.

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