Why this role stands out
This on-site Computational Scientist role offers an exciting opportunity to leverage your expertise in analyzing high-content perturbation screens within a leading biotechnology company, contributing to groundbreaking research and development. If you are a motivated scientist with a PhD and a passion for using computational methods to drive healthcare innovation, you'll thrive in this collaborative environment. Don't miss this chance to grow your skills and make a significant impact.
Quick overview
Job description
The successful candidate will be a highly independent computational scientist with a strong hands-on analytical background in genetic epidemiology, statistical genetics, or computational biology. This role will develop and apply analytical approaches to integrate and interpret genetic, genomic, and clinical data. We are particularly interested in candidates positioned to tackle the integration of multiple sources of human biological data, such as whole genome sequencing and single cell RNA-Seq/ATAC-Seq data, including knowledge of emerging multimodal data integration methods.
Responsibilities:
- Collaborate with scientists in the Human Genetics department to analyze large datasets of genetic, genomic, and clinical data from internal studies, collaborations with academic and industry partners, and public external data sets
- Develop analytical approaches to integrate and interpret these data, delivering insights into disease biology to propel our translational goals
- Implement machine learning algorithms to understand associations between imaging and omics data
- Coordinate the intake and preparation of new datasets as they become available for analysis
- Document process, findings, and code
- Present findings to the department and cross-functional collaborators and contribute to publications
Requirements:
- Extensive experience in large-scale genetic/genomic data analysis including one or more of the following areas of expertise:
- Understanding of principles of genetic epidemiology
- Association analysis with array- and sequence-based genetic data (GWAS - genome-wide association studies) on human data
- Analysis of sequence-based molecular assay data (eg RNA-Seq) including differential expression methods, single-cell sequencing data (eg scRNA-Seq, scATAC-Seq) and/or proteomic data
- Integration of genetic and molecular data for multimodal analyses
- PhD (or Masters with significant experience) in Statistical Genetics, Computational Biology, Bioinformatics, Genetic Epidemiology, or a related field
- Fluent in R, Python, and shell scripting. Some familiarity with C++ will be a plus
- Experience working with git and high performance computing (e.g. the SLURM scheduling manager)
- Curiosity and desire to learn more about human genetics, bioinformatics, and biology
- Ability to produce high-quality analysis results with minimal supervision. This includes meeting key deadlines and making sensible independent decisions
- Good communication skills and experience working as part of a team
Pay range: up to $56.91 per hour
Only candidates available and ready to work directly as Aptask Global Workforce (AGW) employees will be considered for this position.
If you have the described qualifications and are interested in this exciting opportunity, apply today!
Aptask Global Workforce (AGW)
ApTask Global Workforce (AGW) is a certified Minority and Veteran workforce solutions company. AGW delivers operational, clinical, lab and professional talent with a strong focus on healthcare and life sciences. The company supports clients with reliable staffing, program expertise and a commitment to quality, speed and consistent delivery.
Benefits of working with ApTask Global Workforce include:
- Medical
- Dental
- Vision
- Sick Pay (for applicable states/municipalities)
Our team stays close to the process and is here to guide you every step of the way. To learn more, please visit our website
ApTask Global Workforce is an Equal Opportunity Employer. Candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability or status as a protected veteran.
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