Job ID: 40582
Job date: 2017-06-18
End Date:
Company : Stanford Health Care Country : Role : Research Scientist
Job date: 2017-06-18
End Date:
Company : Stanford Health Care Country : Role : Research Scientist
Job Description:
Sr. Staff Scientist - Algorithms will be part of a growing Clinical Genomics team of Bioinformaticians, Lab Scientist, Data Curation Scientists, Clinicians and Medical Fellows. Clinical Genomic Service (CGS) is a collaboration between Stanford Hospitals and Stanford School of Medicine to deliver best-in-class genomics service to Stanford community. CGS plans to use multi-omics (Whole Exome and Transcriptome) analysis approach to diagnosis. This position will be responsible for leading the algorithm development efforts within CGS. Evaluate current algorithms and develop a "best-practice" set of algorithms for use in a clinical diagnostics setting. Guide and mentor other junior members of the algorithm development team. Interface with the Curation team to identify gaps in variant detection and annotation and develop novel algorithms and methods to fill those gaps.
Additional Info:
Job Type: Full Time FTE/Bi-Weekly Hours: 1.0/80 Shift: Days Hours in Shift: 8 Location: Palo Alto Req: 40582 [Click Here to Access the Original Job Post]
Sr. Staff Scientist - Algorithms will be part of a growing Clinical Genomics team of Bioinformaticians, Lab Scientist, Data Curation Scientists, Clinicians and Medical Fellows. Clinical Genomic Service (CGS) is a collaboration between Stanford Hospitals and Stanford School of Medicine to deliver best-in-class genomics service to Stanford community. CGS plans to use multi-omics (Whole Exome and Transcriptome) analysis approach to diagnosis. This position will be responsible for leading the algorithm development efforts within CGS. Evaluate current algorithms and develop a "best-practice" set of algorithms for use in a clinical diagnostics setting. Guide and mentor other junior members of the algorithm development team. Interface with the Curation team to identify gaps in variant detection and annotation and develop novel algorithms and methods to fill those gaps.
- Lead the algorithm development group and efforts with the goal of developing NGS algorithms that serve as NGS community standards.
- Develop novel algorithms for DNASeq and RNASeq for use in a diagnostics setting.
- Develop new and/or improve upon existing algorithms for genome assembly, variant detection (SNPs and InDels) and Structural Variant detection (CNVs, Inversions and Translocations) for clinical grade genomic analysis pipeline.
- Develop and maintain a knowledge database of variants and annotations discovered in processing of samples.
- Develop and maintain a database of public annotation sources such as ClinVar, Exome Variant Server, 1000 Genomes, TCGA and DGV.
- Develop efficient protocols and tools to upload WGS/WES data from internal servers to Cloud Storage (AWS S3/Google Cloud Storage).
- Establish new and leverage existing collaborations with research groups within Stanford and other pre-eminent research institutions.
- Maintain a high public profile within the Clinical and Translational Genomics community through publications and presentations in high impact journals and conferences.
- Help mentor other junior-level bioinformaticians in the group.
- Work closely with the data curators and genetic counselors to help improve the overall solve rate of cases. Perform other related duties as assigned.
- All qualified applicants will receive consideration for employment without regard to race, sex, color, religion, national origin, protected veteran status or on the basis of disability.
Qualifications
Any combination of education and experience that would likely provide the required knowledge, skills and abilities as well as possession of any required licenses or certifications is qualifying. Minimum Requirements:- Education: Graduate Degree (Ph.D, M.S with considerable experience will be considered) in Computer Science/Engineering, Bioinformatics, Mathematics, Statistics and other related fields.
- Experience: Six (6) years of experience with increasing responsibilities, developing algorithms for next generation sequencing (preferably in a Clinical setting).
- Knowledge of algorithmic techniques common to bioinformatics (e.g., dynamic programming and graph algorithms), machine learning and statistical analysis methods (e.g., Bayesian inference, Hidden Markov Models, Principal Component Analysis).
- Experience in developing one or more of the algorithms used in NGS analysis - Sequence alignment, Variant Calling (SNVs), Local-Assembly (De-bruijn graph), and Fusion Detection etc.
- Extensive experience handing error modes in NGS data (preferably Illumina) within STR, long homo-polymers, high GC and other troublesome regions of the human genome.
- Experience in bioinformatics resources such as BLAST, BWA, GATK, dbGaP, Clustalw, NCBI, EBI, Pfam, COG, GO, KEGG, etc.
- Experience in Biomarkers/Genomic markers discovery is a big plus.
- Proficiency in either C/C++ or Java and Linux.
- Familiarity with Perl, Python and R.
- Strong analytical abilities and communication skills.
Requeriments :
- M.Sc. or higher Degree in Bioinformatics
- M.Sc. or higher Degree in Computer Science
- M.Sc. or higher Degree in Statistics
- Master's Degree in Engineering
Skills :
- Biomarker Discovery
- Database design
- Genome Assembly
- genomic
- Lunix/Unix
- Machine Learning
- Next Generation Sequencing
- Programing in C
- Programing in C++
- Programing in Python
- Programming in Java
- Programming in PERL
- Programming in R
- Statistics
Areas :
Additional Info:
Job Type: Full Time FTE/Bi-Weekly Hours: 1.0/80 Shift: Days Hours in Shift: 8 Location: Palo Alto Req: 40582 [Click Here to Access the Original Job Post]