Job Description:
Sema4 Genomics is seeking a talented, self-motivated individual to participate in leading edge research in translational bioinformatics as a member of the R&D Disease Discovery group. A successful applicant will be part of an interdisciplinary team that develops and applies computational methods and databases to integrate and perform analysis on large-scale human genetic and other-omic datasets to better understand Mendelian and complex diseases. A successful applicant may also play a role in developing systems for integrating novel informatics and genomic tools and methodologies into clinical practice. DUTIES AND RESPONSIBILITIES:
Additional Info:
Please submit cv and publication record. [Click Here to Access the Original Job Post]
Sema4 Genomics is seeking a talented, self-motivated individual to participate in leading edge research in translational bioinformatics as a member of the R&D Disease Discovery group. A successful applicant will be part of an interdisciplinary team that develops and applies computational methods and databases to integrate and perform analysis on large-scale human genetic and other-omic datasets to better understand Mendelian and complex diseases. A successful applicant may also play a role in developing systems for integrating novel informatics and genomic tools and methodologies into clinical practice. DUTIES AND RESPONSIBILITIES:
- Support research in disease discovery on internal, pharma and academic collaborations by performing computational analysis of big data collected from patients.
- This computational support will involve working closely with biology researchers to execute specific computational tasks providing the basis for research for publications, internal projects and projects involving external collaborators.
- Analyze the functional impact of genetic variants, and identify variant disease association.
- Analyze high throughput genetic data including whole genome, whole exome, genome-wide genotyping, and RNAseq (bulk and single cell) data.
- Integrate analysis of genetic data and clinical data to understand genetic risks, disease mechanisms, and drug response.
- Generate processing pipelines for gene expression and proteomic data.
- Generate differential expression and gene correlation signatures.
- Construct gene expression co-expression and Bayesian causal networks.
- Mine EMR for gene trait correlation analysis.
- Perform un supervised gene expression clustering analysis.
- Prior experience analyzing next generation sequencing and genotyping data in a high performance computing environment for the analysis of large human molecular biology, genetics and clinical datasets.
- A track record of contributing to biomedical projects using statistical and/or computational approaches.
- Outstanding programming skills with two or more of the following languages: R, Python, Perl, Matlab, Java, C, and/or C++, and UNIX.
- Experience in SQL.
- Experience in machine learning application preferred.
- Strong genomics and genetics background required.
- Outstanding knowledge of public repositories of genetic, genomic, biological and drug data.
- Experience mining EHR data.
- Aptitude for learning and applying new methods.
- Strong ability to collaborate with teams of research scientists, bioinformaticians, software developers, and external collaborators. Experience with meeting deadlines in a fast-paced environment. Strong written and verbal communication skills.
Requeriments :
- M.Sc. or higher Degree in Bioinformatics
- M.Sc. or higher Degree in computational biology
- M.Sc. or higher Degree in Computer Science
Skills :
- Bioinformatics
- Genetics
- genomic
- HPC
- Lunix/Unix
- Machine Learning
- molecular biology
- Next Generation Sequencing
- Programing in C
- Programing in C++
- Programing in Python
- Programing Skills
- Programming in Java
- Programming in Matlab
- Programming in PERL
- Programming in R
- RNA-seq
- SQL
Areas :
Additional Info:
Please submit cv and publication record. [Click Here to Access the Original Job Post]