Bioinformatics and Data Analyst
Clinical Biomarkers Laboratory (CBL) in the Department of Medicine at Emory University is seeking a highly motivated and creative bioinformatician/computational biologist to join the CBL team. This position is responsible for developing algorithms and computational workflows, developing and maintaining software, and analyzing high-throughput metabolomics data using a variety of state-of-the-art statistical and data mining techniques for biomarker discovery and systems biology. This position will contribute to the development and application of computational workflows for processing, analyzing, and visualizing “BIG” metabolomics data. This position will apply statistical and data mining techniques for biomarker discovery, pathway analysis, and integrating multi –omics data. They will present the models in a form that allows users to make decisions concerning the direction of an experimental program. The applicant will perform additional related responsibilities as required. This position will provide opportunities for multiple publications, cross-disciplinary collaborations and experience in integrating metabolomics data with clinical outcomes and other –omics data. The initial appointment is for one year, with renewal expected if progress is satisfactory and funds are available.
- Applicant with a master's degree in bioinformatics, computational biology, biostatistics, or related field.
- Expertise in systems biology, omics data analysis, and experience working with large –omics data (metabolomics and/or transcriptomics)
- Experience with one or more programming languages: R, Python, Perl
- Experience with biological and statistical data analysis, including data mining techniques such as PCA, hierarchical clustering, ANOVA, SVM, PLS, and LIMMA.
- Strong communication skills (both verbal and written) and interpersonal skills to clearly and concisely convey objectives and results to a diverse audience including basic and clinical research scientists.
- Able to multitask and thrive in a fast paced, dynamic, project-driven work environment.
- Familiarity with MySQL/NoSQL and knowledge of relational databases.
- Strong skills with statistical packages in R or other open source software packages to discover patterns, trends, and groups within complex biological data.
- Familiarity with pathway enrichment and network analysis.
- Comfortable using both Linux and Windows platforms.
The research projects that applicant will work for are within the collaborative research of Drs. Dean Jones, Young-Mi Go, and Jessica Alvarez.
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