Deep Learning Engineer

Website Inductiva Research Labs

Contributing to science using Machine Learning

You will be part of a team applying advanced Deep Learning techniques to fundamental problems in Molecular Biology. This can involve dealing with genetic or proteomic datasets, creating ML models that process sequential data about genes and proteins, model their 3d geometry as well as interactions they establish among themselves and with different molecules. You will make use of concepts from Geometric Deep Learning, such as Graph Neural Networks, and try to incorporate physical, geometric and evolutionary priors with other sources of experimental data, into an end-to-end learning architecture.

In this position, you will be spending a lot of your time modeling Biology problems from the perspective of Machine Learning. You will not be alone in this challenge. You will interact with people of different backgrounds, ranging from Computer Science, Mathematics, Physics, to Biology experts. The kind of work you will be doing involves a lot of ML exploration and experimentation. We will be trying to keep the cycle idea-implementation-experiment as agile as possible, by having clear metrics and good ML infrastructure and best-practices in software engineering.

 

(more details on the application link)


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