Organization Overview Genetics has furnished the parts list for vertebrate development but not the instructions necessary to assemble those parts and create an embryo. The Laboratory of Theoretical Condensed Matter Physics, led by Dr. Eric D. Siggia, studies embryonic stem cells from mice and humans using methods derived from biophysics that permit the self-organization potential of stem cells to manifest itself. The assays reveal how signaling pathways integrate cues across space and time to pattern the developing embryo. Overview We seek a highly motivated Bioinformatics Assistant to join the Laboratory of Theoretical Condensed Matter Physics. The primary responsibility will be to process time-lapse datasets of mouse embryos acquired using light-sheet microscopy. Responsibilities Responsibilities include the following: + Use custom Python/MATLAB-based software developed in lab + Correct nuclear segmentations generated by state-of-the-art deep learning models + Classify cell types + Refine lineage tracking trees + Will learn/apply computational geometry techniques to extract 3D embryo structure Qualifications **REQUIRED QUALIFICATIONS:** + Bachelors degree in Computational Biology, Computer Science, Bioinformatics, Biostatistics, Mathematics, or related field **PREFERRED QUALIFICATIONS:** + Interest in biology/ biomedical research + Coding experience The Rockefeller University is an equal opportunity employer veterans/individuals with disabilities. Qualified applicants will receive consideration for employment without regard to characteristics protected by applicable local, state or federal law, including but not limited to disability and protected veteran status. The salary of the finalist selected for this role will be set based on various factors, including but not limited to organizational budgets, qualifications, experience, education, licenses, specialty, and training. The hiring range provided represents The Rockefeller University's good faith and reasonable estimate of the range of possible compensation at the time of posting. Compensation Range: Min USD $50,000.00/Yr. Compensation Range: Max USD $55,000.00/Yr.