Job Listings : Machine Learning engineer: internship

Company : Stanford University
Post Date : 09/08/2017
Type : Part Time

Contact: Noemi Andor nandor@stanford.edu

Machine Learning engineer: internship

Who we are:
Tumor evolution proceeds at a rapid pace. Drug development does not. In order for cancer therapy to achieve a durable response over years rather than months, it must “evolve” as quickly as the tumor does. We develop software solutions that enable data-driven clinical decision making by providing oncologists and specialized tumor-boards with patient specific genomic information. Executing on this mission will rely on a long-term synergy between evolving perspectives on tumor populations and on an interdisciplinary effort to sharpen these perspectives.

Position description:
We are seeking a machine learning (ML) engineer to develop a classifier to distinguish tumor from normal cells. This person will be part of a cross-functional effort to build a ML platform that learns through user interaction to continuously improve its performance at an unprecedented resolution of single cells.
Successful candidate will play a critical role in defining and executing the software’s development strategy. Position initially offered as internship with possible extension upon satisfactory progress.

Candidates should have experience designing, implementing and debugging ML techniques, building high-leverage data infrastructure according to established software architecture principles and be versant in working with imaging data.

The ideal candidate should be an expert in artificial neural networks, in particular LSTM networks and semi supervised learning concepts. Expertise in MATLAB and MagicDraw are a plus. Candidates should demonstrate a strong ability to work cross-functionally and to communicate ideas and results.

Position requirements:
• Strong background developing ML methods and experience in implementing and extending ML algorithms independently
• Experience with artificial neural networks, in particular LSTMs
• Strong skills in software architecture design and substantial expertise in MATLAB and Java
• Strong analytical and quantitative skills
• Experience with imaging data pre-processing is preferred but not required
• BS in Computer Science or related field, or equivalent practical experience