Overview The Sabeti lab at the Broad Institute is seeking a Computational Scientist. Our team has been developing algorithms, machine learning models, and software to design viral diagnostic and sequencing assays. These methods enable rapidly designing effective nucleic acid diagnostics and sensitive metagenomics assays for viruses, including for novel viruses and ones that change considerably over time. The methods for diagnostic assays are linked in a software package, ADAPT, that runs end-to-end using the latest viral genomic diversity as input. Job description We are seeking a computational scientist to grow these methods for assay design, with a focus on ones in ADAPT. The role includes developing, testing, implementing, and applying new algorithms and models for more effectively and quickly designing diagnostic assays than traditional approaches enable, as well as for related applications, such as therapies and vaccines. The candidate will lead a team working on these methods; will oversee and mentor software engineers and trainees who contribute to the methods’ development, software implementation, and applications; and will produce publications describing the results. Requirements PhD in computer science or related field Knowledge and experience with algorithm design and machine learning techniques Fluency in Python and practical experience developing well-designed and well-documented software Experience and interest in viral genomics All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. EEO is The Law - click here for more information Equal Opportunity Employer Minorities/Women/Protected Veterans/Disabled
