What are the responsibilities and job description for the Computational Associate II - Neurobiology and Therapeutics of Psychiatric Disorders position at Broad Institute of MIT and Harvard?
We are seeking a motivated Computational Associate II to join the Sheng research group in the Stanley Center for Psychiatric Research at[1] the Broad Institute of MIT and Harvard.
This group investigates the neurobiological mechanisms of schizophrenia and bipolar disorder using mouse models with strong human-genetic validity. This candidate will collaborate with biologists and geneticists to analyze data across multiple modalities — including transcriptomics, proteomics, high-content behavioral assays, and functional ultrasound imaging—with the goal of identifying convergent and divergent patterns and molecular signatures that shed light on the mechanisms and circuits disrupted in mental illness.
This person will apply existing computational methods, help develop new computational methods where needed, and interpret results within a biological context. This researcher will work in close collaboration with laboratory scientists on analysis of a range of projects with a strong emphasis on bulk, single cell, and spatial RNA-seq approaches. The scope will include integration with other internal and external genomics datasets. The position will provide an opportunity to become a part of the computational biology community at the Broad Institute.
CHARACTERISTIC DUTIES
* Analyze large RNA-Seq datasets to profile transcriptomes from brain and neuronal cell populations, and interpret results to derive important biological insights into these models.
* Work with wet-lab biologists to design and implement appropriate experiments for future computational analysis.
* Provide results in formats accessible to a research community of biologists and geneticists.
* Develop, apply, document, and maintain computational tools, both for own use and to support analysis by biologist colleagues without formal computational training.
* Follow relevant scientific literature to ensure use of optimal methods and understand emerging practices across the field.
* Contribute to reports and papers for presentation and publication and present at scientific conferences, as appropriate.
* Regularly attend and present results at team meetings to share results, plan projects and experiments.
* Work with other Broad computational biologists experienced with RNA-Seq, to learn, discuss, and integrate the most appropriate solution for an experiment or project.
REQUIREMENTS
* BS with 3 years of related experience or MS in Bioinformatics, Computer Science, or other relevant scientific discipline with 1 years of related experience.
* Experience working with RNAseq data.
* Should have a demonstrated proficiency in R and/or Python, or related languages.
* Experience with and solid understanding of statistical analysis is required.
* Familiarity with next-generation sequence data analysis tools, particularly those for RNA-seq
* Understanding of molecular biology and next generation sequencing is highly preferred.
* Familiarity with single cell data analysis is preferred, but not required.
* Familiarity with working on a computing cluster/server (important skills: Unix/Linux, shell scripting)
* Experience designing computational methods and tools, including prior experience with algorithms relevant to computational biology, is a plus.
* Ability to work independently as well as part of an interdisciplinary team in a fast-paced environment, while making necessary connections with experts in various computational analysis groups
* Self-starter, highly motivated.
* Excellent organization and time management skills.
References
Visible links
1. https://www.broadinstitute.org/
This group investigates the neurobiological mechanisms of schizophrenia and bipolar disorder using mouse models with strong human-genetic validity. This candidate will collaborate with biologists and geneticists to analyze data across multiple modalities — including transcriptomics, proteomics, high-content behavioral assays, and functional ultrasound imaging—with the goal of identifying convergent and divergent patterns and molecular signatures that shed light on the mechanisms and circuits disrupted in mental illness.
This person will apply existing computational methods, help develop new computational methods where needed, and interpret results within a biological context. This researcher will work in close collaboration with laboratory scientists on analysis of a range of projects with a strong emphasis on bulk, single cell, and spatial RNA-seq approaches. The scope will include integration with other internal and external genomics datasets. The position will provide an opportunity to become a part of the computational biology community at the Broad Institute.
CHARACTERISTIC DUTIES
* Analyze large RNA-Seq datasets to profile transcriptomes from brain and neuronal cell populations, and interpret results to derive important biological insights into these models.
* Work with wet-lab biologists to design and implement appropriate experiments for future computational analysis.
* Provide results in formats accessible to a research community of biologists and geneticists.
* Develop, apply, document, and maintain computational tools, both for own use and to support analysis by biologist colleagues without formal computational training.
* Follow relevant scientific literature to ensure use of optimal methods and understand emerging practices across the field.
* Contribute to reports and papers for presentation and publication and present at scientific conferences, as appropriate.
* Regularly attend and present results at team meetings to share results, plan projects and experiments.
* Work with other Broad computational biologists experienced with RNA-Seq, to learn, discuss, and integrate the most appropriate solution for an experiment or project.
REQUIREMENTS
* BS with 3 years of related experience or MS in Bioinformatics, Computer Science, or other relevant scientific discipline with 1 years of related experience.
* Experience working with RNAseq data.
* Should have a demonstrated proficiency in R and/or Python, or related languages.
* Experience with and solid understanding of statistical analysis is required.
* Familiarity with next-generation sequence data analysis tools, particularly those for RNA-seq
* Understanding of molecular biology and next generation sequencing is highly preferred.
* Familiarity with single cell data analysis is preferred, but not required.
* Familiarity with working on a computing cluster/server (important skills: Unix/Linux, shell scripting)
* Experience designing computational methods and tools, including prior experience with algorithms relevant to computational biology, is a plus.
* Ability to work independently as well as part of an interdisciplinary team in a fast-paced environment, while making necessary connections with experts in various computational analysis groups
* Self-starter, highly motivated.
* Excellent organization and time management skills.
References
Visible links
1. https://www.broadinstitute.org/
