We are focused on providing our postdocs with opportunities to develop themselves as researchers, exposing them to cutting edge methodology and world leading collaborative science. We are always keen to hear from enthusiastic and curious scientists - please get in touch to learn more about what opportunities we currently have to support potential postdocs.
We're looking for an exceptional scientific writer and editor to play a key role in the Stanley Center for Psychiatric Research (SC) at the Broad Institute. The Stanley Center aims to exploit the most advanced technologies for human genetic analysis to study psychiatric disorders in order to understand disease mechanisms, identify potential biomarkers, and ignite needed progress in therapeutics. The Stanley Center is organized into intellectually porous teams based on principal disciplinary areas of focus including: Genetics, Stem cell-based models, Neurobiology and animal models, Technology development and genome-scale neurobiology, Therapeutics, and Clinical trials. In this position, you will work to contribute intellectually to major research initiatives. We are hoping to find a scientific writer who can be a resource for the SC broadly to help with translating our exciting research into everything from grant applications, annual reports, manuscripts and website content. You'll also engage with a growing community of writers at the Broad to diversify your skills and make connections between projects.
Associate Computational Biologist
We are looking for a highly motivated individual to join the Stanley Center for Psychiatric Research at the Broad Institute. This person will be responsible for integrating and analyzing GWAS, whole exome sequencing and whole genome sequencing data, and for interpreting genetic association results in the context of deeply phenotyped data sets. The candidate should have a strong computational background and demonstrated knowledge of research methods, and be able to adapt quickly and be part of a cross-functional team in a rapidly changing environment. The Stanley Center and the Broad Institute provide a vibrant multidisciplinary research environment with close links to MIT, Harvard and the Harvard-affiliated hospitals across Boston. As a member of our team, you will be provided the opportunity for your contributions to be utilized and recognized across the vast global network of researchers in the fields of genomics and psychiatric disease research.
Software Engineer - Hail Team
We are a small team of software engineers, mathematicians and computational biologists having outsized impact. Our open-source framework Hail (https://hail.is) is already being used to analyze the largest genetic data sets in existence. We are seeking software engineers at several experience levels to join our growing team.
We believe there is a unique opportunity to transform the practice of computational biology by applying deep ideas from computer science and mathematics to build the next generation of modular, scalable tools for analyzing massive genetic and biological data. These tools are needed to unravel the genetic architecture of disease and drive the development of new treatments and biotechnologies.
We implement distributed inference algorithms on top of our custom-built language, compiler, and run-time system to support querying, aggregation, and linear algebra on hundreds of thousands of human genomes. The typical dataset is now tens of terabytes and doubling every eight months. Our challenges are diverse: language and compiler design, low-level performance optimization, architecture of distributed systems, scaling established methods and inventing new ones, visualization, interoperability with other powerful tools, and close engagement with the amazing science and scientists all around us.
Associate Softare Engineer - Hail team
Biology is increasingly data-intensive. We believe there is a unique opportunity to transform the practice of computational biology by applying deep ideas from computer science and applied mathematics to build the next generation of modular, scalable tools for analyzing massive genetic and biological data. These will be critical to unravel the genetic architecture of disease and drive the development of new treatments and biotechnologies. We are a small team of software engineers, mathematicians and computational biologists having outsized impact.
Our open-source framework, Hail, is already being used to analyze the largest genetic data sets in existence. We are seeking software engineers at several experience levels to join our growing team. In addition to software development, our group is interested in the application of machine learning to problems in biology. We run the Models, Inference and Algorithms Initiative at the Broad Institute, bringing together members of the biology and math / stat / ml / cs communities across MIT, Harvard, and Boston to spark collaboration between these fields. To learn more, go to http://www.broadinstitute.org/mia
Data Intake administrator
We are looking for a Data Intake Administrator to join the collaborative and multidisciplinary team of the Stanley Center for Psychiatric Research (SC) at the Broad Institute.
A major scientific collaboration in which the SC plays a central role is the Psychiatric Genomics Consortium (PGC), whose core mission to aggregate and analyze genetic data to advance our understanding of the causes and potential treatments of psychiatric disease. These efforts are continuing to expand, in terms of datasets, number of diseases and the number of researchers who participate in this effort. The PGC's international reputation and demonstrated success attracts more and more potential collaborators who are eager to join the consortium by sharing samples from their own studies. Given the increased scale of these activities and expansion across a wide range of psychiatric disorders, we see the need for the appointment of a new position, the Data Intake Administrator (DIA).
The Data Intake Administrator will be a dedicated person to be responsible for the entirety of this process and will improve the efficiency of PGC operations by creating a smooth flow of new data to the analyst groups to further the computational aspects of genetic data science.