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Join COSINE Lab

The COmputational Signal INformatics and Exploration (COSINE) Lab develops cutting-edge AI and signal-processing methods to decode and understand complex biomedical and natural signals. Our research spans brain–computer interfaces, human–machine interfaces, automated sleep analysis, clinical EEG analysis, and pathological speech processing. We aim to bridge the gap between artificial intelligence research and real-world healthcare impact through collaborative science and open innovation. Before writing to us, please explore our Publications and Research pages to understand our scope and expectations.

To apply: email ayush.tripathi@iiti.ac.in with the subject line Application - [Role] - [Your Name] describing your interests and your CV.

Open Roles

Postdoctoral Researchers

  • PhD in EE/CS/BME or related field with a strong publication record
  • Experience in signal processing and deep learning
  • Experience with EEG/PSG/speech or adjacent modalities is a plus
  • Funding: external fellowships

Email: ayush.tripathi@iiti.ac.in

PhD Candidates

  • Strong background in signal processing and/or machine learning
  • Comfortable with Python, PyTorch/TensorFlow, and MNE/NumPy/Scipy
  • Apply through IIT Indore admissions; email us beforehand to discuss fit
  • Attach CV and a short research statement

Email: ayush.tripathi@iiti.ac.in

IIT Indore UG/PG Students

  • For BTP/MTP/independent study and course projects tied to lab themes
  • Prior experience with signals or ML/DL preferred but not mandatory
  • Include a list of relevant courses and any prior projects (GitHub if available)
  • Expected commitment: consistent weekly progress and documentation

Email: ayush.tripathi@iiti.ac.in

Research Interns (External)

  • Exceptional candidates from other institutes looking to gain practical experience
  • Typical duration: 2–6 months; remote possible for select projects
  • Typically self-funded
  • Share CV, transcripts, GitHub, goals, and preferred dates

Email: ayush.tripathi@iiti.ac.in

What We Value