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 bioinformatics group. The successful applicant will be part of an interdisciplinary team that develops and applies computational methods and databases for personalized diagnosis and therapy of human Mendelian diseases and cancers. This includes the application of machine learning, artificial intelligence and advanced statistical techniques to analyze large scale genetics and biomolecular datasets as well as third party databases. Additional knowledge is extracted from the biomedical literature via natural language processing techniques. This work will also play a role in developing systems for integrating novel informatics and genomic tools and methodologies into clinical practice. DUTIES AND RESPONSIBILITIES:
Additional Info:
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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 bioinformatics group. The successful applicant will be part of an interdisciplinary team that develops and applies computational methods and databases for personalized diagnosis and therapy of human Mendelian diseases and cancers. This includes the application of machine learning, artificial intelligence and advanced statistical techniques to analyze large scale genetics and biomolecular datasets as well as third party databases. Additional knowledge is extracted from the biomedical literature via natural language processing techniques. This work will also play a role in developing systems for integrating novel informatics and genomic tools and methodologies into clinical practice. DUTIES AND RESPONSIBILITIES:
- Develop and implement text mining and machine learning methods to analyze literature for genetic variant recognition, variant normalization, understanding the functional impact of genetic variants, and identifying variant-disease associations.
- Analyze high-throughput genetic data including whole genome, whole exome, and genome-wide genotyping data. Integrative analysis of genetic data and clinical data to understand genetic risks, disease mechanisms, and drug response.
- Develop and maintain collaborations both within the company and with outside researchers in academia and industry.
- Deep expertise in biostatistics, machine learning and text mining methods and applications, specifically targeted towards genetic variant analysis
- Prior experience analyzing and interpreting next generation sequencing and genotyping data
- Experience in the analysis of large human molecular biology, genetics and clinical datasets
- A track record of leading biomedical projects using statistical or computational approaches
- Outstanding programming skills with two or more of the following languages: R, Perl, Python, Matlab, Java, C, and/or C++
- Extensive experience in SQL programming, RDBMS, and ETL tools
- Strong knowledge of Unix shell scripting
- Strong genomics and genetics background required
- Outstanding knowledge of public repositories of genetic, genomic, and biological data
- Strong ability to collaborate with teams of research scientists, bioinformaticians, software developers, and external collaborators
- Experience with meeting deadlines in a fast-paced environment
- Experience with projects related to personalized medicine (preferred)
Requeriments :
- M.Sc. or higher Degree in Bioinformatics
- M.Sc. or higher Degree in computational biology
- M.Sc. or higher Degree in Computer Science
- Master’s Degree in Genetics
Skills :
- Biostatistics
- Genetics
- genomic
- 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
- Shell scripting
- SQL
- Statistics
Areas :
Additional Info:
[Click Here to Access the Original Job Post]