Job Description:
The Broad Institute of MIT & Harvard, a world leader in genetic research, is looking for exceptional candidate(s) to join the Daly Laboratory. The successful candidate(s) will join an interdisciplinary team of computational biologists, bioinformatics analysts laboratory scientists and clinicians who are working together to discover and interpret the genetic variation giving rise to common human disease. We currently have large-scale gene discovery efforts targeted towards neuropsychiatric disease, inflammatory bowel disease as well as parallel, related efforts to comprehensively study phenotypes across population biobank and medical registry data in Finland. The candidate will join a team to develop and implement computational methods for complex disease genetic mapping and interpretation through transcriptome data. Responsibilities will include the development of statistical methods for use in large-scale genetic analyses, to implement aggregation and joint analysis of publicly available gene expression data for the interpretation of genetic results, and to develop user-friendly interfaces that provide access to the broader community to these analyses and their results, and to collaborate with software engineers who are developing computational tools. Key Responsibilities:
Additional Info:
EOE / Minorities / Females / Protected Veterans / Disabilities [Click Here to Access the Original Job Post]
The Broad Institute of MIT & Harvard, a world leader in genetic research, is looking for exceptional candidate(s) to join the Daly Laboratory. The successful candidate(s) will join an interdisciplinary team of computational biologists, bioinformatics analysts laboratory scientists and clinicians who are working together to discover and interpret the genetic variation giving rise to common human disease. We currently have large-scale gene discovery efforts targeted towards neuropsychiatric disease, inflammatory bowel disease as well as parallel, related efforts to comprehensively study phenotypes across population biobank and medical registry data in Finland. The candidate will join a team to develop and implement computational methods for complex disease genetic mapping and interpretation through transcriptome data. Responsibilities will include the development of statistical methods for use in large-scale genetic analyses, to implement aggregation and joint analysis of publicly available gene expression data for the interpretation of genetic results, and to develop user-friendly interfaces that provide access to the broader community to these analyses and their results, and to collaborate with software engineers who are developing computational tools. Key Responsibilities:
- Statistical analysis and methods development for the joint analysis of DNA variation and clinical phenotype data
- Implementation and optimization of published statistical methods
- Acquisition, organization and harmonization of RNA sequencing datasets from diverse sources
- Development of analytic tools for the analysis of RNA sequencing data and in particular, the integration and interpretation of genetic variation associated to common disease
- Development of browsers and user-friendly web interfaces for both genetic mapping in biobanks and the meta-analysis across RNA sequencing data sets
- Providing support to chemists and biological researchers to interpret results of analyses and to aid in the use of newly developed tools
- Lead and contribute to manuscript preparation as well as internal and external project-team reports.
- Actively participate and present in project team meetings.
- Ph.D. or equivalent work experience in computer science, mathematics, statistics, bioinformatics, or other quantitative discipline required. 2+ years experience with biological datasets.
- Relevant experience or formal training in computational biology, bioinformatics, machine learning or statistics.
- Must have demonstrated proficiency with several of the following technologies: R, Unix, Perl, Python, Java, Matlab, C, C++.
- Familiarity with genetic variation and RNA sequencing data analysis tools strongly preferred.
- Must have demonstrated experience designing user-friendly computational methods and tools, preferably with prior experience with algorithms relevant to computational biology.
- Skill and experience with statistical analysis is strongly preferred.
- Demonstrated capability as highly organized, a creative problem-solver, detail-oriented, self-motivated, and able to work independently as well as within cross-functional teams; experience working in an interdisciplinary team with laboratory scientists and clinicians is a plus.
- Ability to adapt to rapidly changing and high-demand environments.
- Exceptional communication skills (oral and written).
Requeriments :
Skills :
- Bioinformatics
- Computational Biology
- Lunix/Unix
- Machine Learning
- Programing in C
- Programing in C++
- Programing in Python
- Programming in Java
- Programming in Matlab
- Programming in PERL
- Programming in R
- RNA-seq
- Statistics
Areas :
Additional Info:
EOE / Minorities / Females / Protected Veterans / Disabilities [Click Here to Access the Original Job Post]