Predicting Antibody Structure Using Deep Learning

This is a paid opportunity. In order to be eligible to apply for this project, you need to be part of the Omdena community and have finished at least one AI Innovation Challenge.

You can find our upcoming AI Innovation Challenges at https://omdena.com/projects.

The problem

This EVQLV-Omdena project aims to build a deep learning model that takes as input the protein sequence of an antibody and predicts the distance and angle matrices of the antibody structure.

The project goals

• The model should be built using Tensorflow or Keras.
• Using open-source data (tabular, structural data)
• The team will be following an existing implementation (paper).

**More details will be shared once the project is joined.

Why join? The uniqueness of Omdena Top Talent Projects

Top Talent opportunities come as a natural next step after participating in Omdena’s AI Innovation Challenges.

Everyone in the community is eligible to participate once they have shown the relevant skills based on the merit of involvement in past Omdena challenges and the community.

If you are looking for the next challenge after participating in one or more Omdena AI Innovation Challenges, then we believe you have made the right choice! With a healthy, pressured environment, you will be pushed to contribute, learn and grow even more.

Find more information on how an Omdena Top Talent Program works