IIT Madras Robert Bosch Centre invites applications for postdoctoral fellowship; Check details here

IIT Madras Robert Bosch Centre invites applications for postdoctoral fellowship; Check details here

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Anupama Mehra
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New Delhi, Updated on Aug 17, 2020 15:57 IST

The fellowship is open for the candidates from across the country having PhD degree in research topics related to data science, Artificial Intelligence (AI), or applied application domains. 

The Robert Bosch Centre for Data Science and Artificial Intelligence (RBC DSAI) at the Indian Institute of Technology (IIT) Madras is now inviting applications for its postdoctoral fellowship. The fellowship is open for the candidates from across the country having PhD degree in research topics related to data science, Artificial Intelligence (AI), or applied application domains. 

The fellowship will help candidates to carry out independent research, not necessarily attached to a single faculty lab. Candidates who have their thesis under review can also apply. Selected fellows will also get to work with leading faculty in data science and Artificial Intelligence. They will also get additional allowances for research and travel, regular workshops and colloquia by international experts, and access to state-of-the-art high-performance computing infrastructure.

Those who will be selected will also get a monthly stipend. However, the amount of stipend has not been disclosed by the institute yet. IIT-Madras had earlier informed that it can range between Rs 40,000 and 60,000 per month. The RBC-DSAI is one of the few centres in the world for data science and AI applications in various engineering disciplines.

While talking about the fellowship, Professor B Ravindran, Head, RBC DSAI, said, “For fresh PhDs looking for an opportunity to explore new ideas and challenge the limits of what we know in data science, RBCDSAI is willing to invest in their ideas, in the form of a post-doctoral fellowship.”

RBC-DSAI, claims the IIT Madras, is one of the largest groups in India looking at networked data across different disciplines and the top Deep Reinforcement Learning group.

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Anupama Mehra
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