Postdoctoral Associate | Beck Lab

The Beck Lab is seeking an enthusiastic independent and highly motivated postdoctoral fellow to join our innovative research group at the Jackson Laboratory for Genomic Medicine and University of Connecticut Health Center in Farmington CT. The Beck lab uses and develops genomic and transcriptomic techniques to identify variation within repetitive and complex regions of mammalian genomes. As a postdoctoral fellow in the Beck lab you would lead projects examining the mechanisms and consequences of structural variants across human and mammalian organisms.

To accomplish these goals the fellow will analyze existing genomic and transcriptomic data with computational tools to identify novel loci of interest and will execute laboratory experiments to test the consequences of genomic variation. Fluency with multiple experimental techniques coupled with ability or a willingness to learn Python or R and common bioinformatics tools is required to carry out analyses and prepare results for publication. Experience with cell culture and in particular iPSCs will be beneficial for these projects.

Key Responsibilities:

• Conduct cell culture molecular biology and biochemistry experiments
• Maintain lab equipment reagents and follow safety protocols
• Author manuscripts and grant applications
• Present results at lectures and conferences
• Use bioinformatics tools to analyze genomic and transcriptomic data from human and mouse samples
• Interpret variation variant mechanisms and the effect of variants on transcription
• Contribute to project planning and implementation
• Perform data curation and maintain documentation
• Generate reproducible analysis and properly use statistics to support observations
• Collaborate with a multidisciplinary team of researchers who perform bench and computational experiments

Preferred/bonus skills:

• Experience with iPSC culture and differentiation
• Knowledge of structural variation and variant mechanisms
• Experience using computational libraries for tabular data and statistical analysis
• Experience executing jobs and pipelines in a high-performance computing cluster
• Experience working in a Linux command-line environment

Qualifications:

• PhD in Physiology Molecular Biology Genetics Biomedical Engineering or a related field
• Strong publication record in peer-reviewed journals
• Excellent communication and teamwork skills with the ability to work independently and collaboratively
• Experience using statistical inference to support results

Application Instructions: Please submit your current CV at least 2 letters of reference and a 1-page (maximum) statement

JAX Salary:

Year 0 - 1: $65589

Year 1 - 2: $67318

Year 2 - 3: $69095

Year 3 - 4: $70521

Year 4 - 5: $72877

Year 5 - 6: $75569

Based on years of experience as Postdoc

About JAX:

The Jackson Laboratory is an independent nonprofit biomedical research institution with a National Cancer Institute-designated Cancer Center and nearly 3000 employees in locations across the United States (Maine Connecticut California)Japan andChina. Its mission is to discover precise genomic solutions for disease and empower the global biomedical community in the shared quest to improve human health.

Founded in 1929 JAX applies over nine decades of expertise in genetics to increase understanding of human disease advancing treatments and cures for cancer neurological and immune disorders diabetes aging and heart disease. It models and interprets genomic complexity integrates basic research with clinical application educates current and future scientists and provides critical data tools and services to the global biomedical community. For more information please visit.

EEO Statement:

The Jackson Laboratory provides equal employment opportunities to all employees and applicants for employment in all job classifications without regard to race color religion age mental disability physical disability medical condition gender sexual orientation genetic information ancestry marital status national origin veteran status and other classifications protected by applicable state and local non-discrimination laws.