Job Description:
We look for talented and self-motivated computational biologists to join our team to study human disease using large-scale omics datasets. The projects will involve analyzing DNA and RNA data, elaborating deconvolution of cell populations and associated cellular phenotypes, integrating mult-level omics data, with the goals to develop molecular patterns for diagnostics and predictive markers for treatments. The candidate should have a Ph.D. in Computational Biology, Biostatistics, Bioinformatics, or related field, and have interests working in an interdisciplinary field of computational genomics and immunology. The candidate should have extensive working experience analyzing large-scale transcriptomic data and are capable of designing and implementing new/existing algorithms. Applicants shall have excellent programming skills in one scripting language (Perl, Python, etc) and one data analysis software (R, MATLAB, etc), and be proficient in English, both written and spoken, as well as good communication skills.
Additional Info:
The research of our computational genomics lab at Stanford Genome Technology Center aims at pushing the boundaries of genomics technology from base pairs to bedside. At the center, we are closely involved in the development of biotechniques from their early stage pilot studies to the demonstration applications. We use computation in experimental design, data analysis, troubleshooting, and improving the performance of the technology. The major bottleneck of genomic medicine is no longer data generation but the analysis and interpretation of 'big data' acquired. We develop computational, bioinformatic, and statistical approaches to addressing the challenges in large-scale studies of the genomics, proteomics and metabolomics of diseases. In particular, we focus on systems biology of immune and metabolic responses, which are important in many diseases from cancers and infections, by integrative analysis and modeling of the molecular, cellular, organ functional, and clinical information from patients and disease models. How to apply? Please send your CV, contact information of three references, and a cover letter to Dr. Wenzhong Xiao, [Click Here to Access the Original Job Post]
We look for talented and self-motivated computational biologists to join our team to study human disease using large-scale omics datasets. The projects will involve analyzing DNA and RNA data, elaborating deconvolution of cell populations and associated cellular phenotypes, integrating mult-level omics data, with the goals to develop molecular patterns for diagnostics and predictive markers for treatments. The candidate should have a Ph.D. in Computational Biology, Biostatistics, Bioinformatics, or related field, and have interests working in an interdisciplinary field of computational genomics and immunology. The candidate should have extensive working experience analyzing large-scale transcriptomic data and are capable of designing and implementing new/existing algorithms. Applicants shall have excellent programming skills in one scripting language (Perl, Python, etc) and one data analysis software (R, MATLAB, etc), and be proficient in English, both written and spoken, as well as good communication skills.
Requeriments :
Skills :
- genomic
- immunology
- Programing in Python
- Programing Skills
- Programming in Matlab
- Programming in PERL
- Programming in R
- Transcriptomics
Areas :
Additional Info:
The research of our computational genomics lab at Stanford Genome Technology Center aims at pushing the boundaries of genomics technology from base pairs to bedside. At the center, we are closely involved in the development of biotechniques from their early stage pilot studies to the demonstration applications. We use computation in experimental design, data analysis, troubleshooting, and improving the performance of the technology. The major bottleneck of genomic medicine is no longer data generation but the analysis and interpretation of 'big data' acquired. We develop computational, bioinformatic, and statistical approaches to addressing the challenges in large-scale studies of the genomics, proteomics and metabolomics of diseases. In particular, we focus on systems biology of immune and metabolic responses, which are important in many diseases from cancers and infections, by integrative analysis and modeling of the molecular, cellular, organ functional, and clinical information from patients and disease models. How to apply? Please send your CV, contact information of three references, and a cover letter to Dr. Wenzhong Xiao, [Click Here to Access the Original Job Post]