End-to-end Deep Learning Pipelines for Cancer Genomic Data

Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB), Politecnico di Milano
August 28 2017
Position Type
Full Time
Organization Type

The development of machine learning pipelines specific to genome sequence analysis is crucial to the currently rapid development of personalized medicine, and big data are already available for the analysis. Most of the focus is on the particular methods of the statistical analysis, but only a relatively small fraction is aimed at developing of end-to-end deep learning pipelines containing these specific methods as integrated components. The particular focus of the research project on the development of the end-to-end deep learning pipeline for cancer detection in genetic data. The ideal candidates are expected to possess both a certain background in molecular biology and genetics as well as experience in development of the deep learning systems.

This job comes from a partnership with Science Magazine and Euraxess