Source:-telanganatoday
This Research Fellowship provides a unique opportunity to carry out independent research, not necessarily attached to a single faculty lab, for PhDs who want to mature towards an independent research career.
Hyderabad: The Robert Bosch Centre for Data Science and Artificial Intelligence (RBC DSAI) at IIT Madras has invited applications for its Post-Doctoral Fellowship. It is open to candidates across the country with PhD Degrees in Research Topics related to Data Science, Artificial Intelligence or allied application domains.
This Research Fellowship provides a unique opportunity to carry out independent research, not necessarily attached to a single faculty lab, for PhDs who want to mature towards an independent research career.
It also includes a monthly stipend that is significantly higher than typical institute Post-Doctoral Fellowships. The RBC-DSAI is one of the few centres in the world for Data Science and AI applications in various engineering disciplines.
The eligibility criteria include academic qualifications, outstanding publication record and proficiency in programming (high-level languages, preferably Python / R / MATLAB). Contributions to open-source projects will be advantageous. Candidates with their thesis under review can also apply.
RBCDSAI plays a vital role in enhancing fundamental and applied research in data sciences. In addition to a creative and interdisciplinary work environment, with state-of-the-art high-performance computing infrastructure, RBC also offers additional allowances for research and travel, and an opportunity to mentor brightest of students—thus reflecting the flavour of real research.
RBC-DSAI at IIT Madras is the leading interdisciplinary Data Science and AI centre in India and one of the few centres in the world focussing on applications in various engineering disciplines. It has one of the largest groups in India looking at networked data across different disciplines and the top Deep Reinforcement Learning group.
The Areas of research include Deep Learning, Network Analytics, Theoretical Machine Learning, Reinforcement Learning and Multi-armed Bandits, Natural Language Processing, AI on the edge, System Architecture for Data Science and AI, Ethics, Fairness and Explainability in AI, Systems Biology and Healthcare, Smart Cities and Transportation, and Financial Analytics.
