The project will involve both theoretical work on designing machine learning tools for the biophysical questions, and also implementing and evaluating these tools. Familiarity with practical machine learning is one of the main skills we are looking for, but some background in computational mathematics would be a plus.

Requirements

1. Familiarity with the use of computational frameworks such as Torch/​Tensorflow, scikit-learn, numpy/​scipy.
2. Understanding of standard statistical and machine learning techniques.
3. Willingness to pick up details of biophysical aspects of the problems being studied. Prior experience in computational biology/​computational chemistry would be a plus.

The appointment would be for an initial period of 1 year, renewable for an additional period of 6 months to a year upon review.

Compensation will be commensurate with qualifications and experience of the selected candidate as well as the level at which they are hired, and will be in accordance with existing TIFR norms.

PhD (for appointment as a postdoctoral scholar) / undergraduate degree (for appointment as a research fellow) in a relevant field, e.g. Computational Biology/​Chemistry/​Physics, Mathematics, Statistics, Computer Science, Engineering etc., with experience in computational methods.

Interested candidates should email Dr. Shachi Gosavi at the email address: shachi@​ncbs.​res.​in, with the subject line “[rna-project] Postdoc application: <name> (for candidates with a PhD degree) or “[rna-project] Research Fellow application: <name> (for candidates without a PhD degree). (The string “<name>” should be replaced by the candidate’s name.)

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