The ideal candidate will have:
A PhD/post doc within the computer sciences with several years of work experience
Familiarity with most of the standard methods: linear regression, logistic regression, decision trees, random forest, neural networks, nearest neighbours, support vector machines, lasso, deep learning - including deep neural networks and deep belief networks.
You need to have experience with developing and training both classical machine learning techniques as well as more advanced deep learning algorithms.
Publications within the field are considered a plus.
Previous experience with drug discovery and translational science from the pharmaceutical industry/biotech is a plus but is not a requirement.
The job requires proficiency in English and excellent communication and collaboration skills.
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