[SocBiN] Computational scientist position - Algorithms for structural variation discovery from long reads - Broad Institute of MIT and Harvard

[Fabio Cunial]

The Long Reads group, within the Data Sciences Platform at the Broad
Institute in Cambridge, MA, is looking for two method developers to join
its efforts in discovering structural variants from tens of thousands of
long-read samples from human individuals, and in genotyping structural
variants on millions of short-read samples.

The ideal candidate for the first position has experience in designing
algorithms and data structures on sequences, in implementing them at scale,
and preferably an appreciation of the complexities of real data and a
significant background in computational biology. Previous experience in
algorithms/data structures for pangenomes, or in genome assembly, would be
very useful.

The second position requires expertise in machine learning and statistics,
including deep learning, and concrete previous experience in designing and
deploying learning algorithms at scale (not necessarily in genomics).

Our data comes from the All of Us Research Program (https://allofus.nih.gov)
and from several other partnerships with sequencing centers and research
groups. Our team tackles methods development needs arising from long-read
data across the Broad, and is connected to groups in the Broad community
and to clinical and academic researchers worldwide. For more details about
the position, see e.g.:

https://www.linkedin.com/jobs/view/computational-scientist-long-reads-group-at-broad-institute-of-mit-and-harvard-3163620369

If interested, please send your CV, a list or publications, and a cover
letter that explains how your profile fits the position, to Fabio Cunial (
fcunial at broadinstitute.org), or use the application form at the link above.
Feel free to contact Fabio for any other questions you might have.
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