The Center for Proteomic Chemistry (CPC) at the Novartis Institutes for BioMedical Research (NIBR) has an exciting opportunity for a Ph.D. level computational scientist to join the in silico lead discovery group (iSLD) in Cambridge, USA.
As a member of the global iSLD team, your primary responsibility will be to develop and apply image analysis methodologies and workflows involving multidimensional data (time series, 3D volumes, etc.) over a wide range of image modalities generated from large-scale, small molecule screening. In this role you will be working closely with a highly innovative team in lead discovery.
The candidate must be able to work independently to define the specific parameters to be modeled and to apply and evaluate the results of analysis of cellular and subcellular high-content images. In addition you should also be able to investigate, develop and optimize methods and workflows that leverage targeted and distributed high performance computing resources to deliver image analysis for large data volumes.
As part of an early drug discovery research team you are expected to be able to clearly and thoroughly document all modeling and analysis activity, to have a thorough understanding of the physical principals underlying the modeling tools, and be able to discuss and explain how these results can be interpreted with respect to the context of the biological experiment.
Essential capabilities in raw image analysis are: feature recognition, object tracking, vector and time series analysis from video, 3D imaging (z-stacks), image enhancement, metadata analysis, image conversion, filtering, segmentation and higher dimensional datasets (3D + time).
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