Computer/Data Scientist, Preclinical modeling, Imaging & Testing Core (PMIT) at MIT Koch Institute

Posting for a friend. Job Type: Full-time

Full Job Description

Working at MIT offers opportunities, an environment, a culture – and benefits – that just aren’t found together anywhere else. If you’re curious, motivated, want to be part of a unique community, and help shape the future – then take a look at this opportunity.

COMPUTER/DATA SCIENTIST, PRECLINICAL MODELING, IMAGING & TESTING CORE (PMIT) , Koch Institute for Integrative Cancer Research, to join an interdisciplinary team at the Preclinical Imaging and Testing Facility (Preclinical I&T), dedicated to offering minimally-invasive and imaging-based tools to the research community for the evaluation of novel therapies. Will collaborate on evaluating and expanding a library of publicly available image processing tools and models and assessing them for use with the facility’s preclinical data models; deploy an analytics workflow that is transferrable between clinical and preclinical imaging data; develop user-friendly pipelines for image segmentation, classification, and -omics analytics; develop custom-made image processing and quantification tools; oversee the facility’s computational suite and expand on the available computational resources; work with staff to create a common multimodal software pipeline for automated, time-efficient image analysis and decision-making; create and present data analysis case studies and tutorials; and collaborate with other MIT departments to develop and optimize imaging tools.

Job Requirements
REQUIRED : advanced degree (M.Sc./Ph.D.) in a quantitative discipline; three years’ (if M.Sc.) post-degree work experience in data-rich projects in academia/industry; experience with machine learning frameworks and wrappers (e.g., TensorFlow, MxNet, Keras, Caffe, Pytorch, Flux); familiarity with common deep network architectures for image processing (e.g., UNet, VNet, RNNs); understanding of machine learning concepts (e.g., object recognition, natural language processing, transfer learning, regression and classification); mastery of at least one scientific computing and numerical analysis language (e.g., R, Julia, Python, C), preferably Julia; willingness to learn Julia; experience with data management, organization and numerical computing; and familiarity with image visualization and processing software (e.g., Amira/Avizo, Slicer, Osirix, ImageJ, VivoQuant, Amide). PREFERRED : computer science background, familiarity with web development, and knowledge of preclinical imaging technologies/applications.

For more details see: