IIT Madras through its Robert Bosch Centre for Data Science and Artificial Intelligence (RBCDSAI) is offering yet another internship to students in their final year undergraduation or postgraduation. The online internship will be of three to six months duration and selected candidates will also be paid a monthly stipend of Rs 10,000. This opportunity is open to Indian students only, and the internship will begin in either May or June.
Applicants will need to have a minimum CGPA of 3 out of four or eight out of ten and a Python programming test will be held for all applicants after clearing the initial screening process. Also, for certain projects, additional rounds such as MCQs on machine learning, data science and artificial intelligence may be held. After clearing the initial rounds, an interview could be scheduled with the project team.
How to Apply for IIT Madras Online Internship
Interested students may apply by submitting the required information on the Google form before 5 May 2021. Apart from submitting the form, the following information will also need to be submitted:
- Statement of purpose: Why you would like to do an internship at RBCDSAI? What is your preparation for the area? What are the projects you would like to work in? Why did you pick those specific projects?
- Curriculum vitae.
- Letter of recommendation must be mailed to firstname.lastname@example.org, with the candidate’s name in the subject line.
Topics Available for IIT Madras Online Internship
Students can choose up to three topics from the following list:
- Structural characterization of algebraic tournaments.
- The interconnection of adaptive modules/motifs.
- Network mapping.
- Automated doubt generation models for natural language contexts.
- AI based acoustic camera based gesture recognition.
- Simulation assisted AI based automation of X-ray baggage scanning.
- AI based simulations in wave propagation.
- Identification of putative driver genes and their role based on patient profile.
- Artificial intelligence for energy management and optimization in smart buildings.
- Knowledge augmented real-estate description generation.
- Dropout prediction in MOOCs.