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Oak Ridge Institute for Science and Education · 3 months ago

WRAIR - Postdoctoral Fellow in Viral Genomics, Bioinformatics, Machine Learning and Artificial Intelligence

Silver Spring, MD

Full-time

Onsite

New Grad

$70K/yr - $80K/yr

The Oak Ridge Institute for Science and Education is offering a postdoctoral-level fellowship at the Walter Reed Army Institute of Research (WRAIR) focused on infectious disease research. The role involves engaging in projects related to genomic surveillance and viral evolution, utilizing advanced computational methods and fostering independent research skills.

Government Administration

No H1B

U.S. Citizen Only

Responsibilities

Developing new computational methods and analytical tools, with particular emphasis on machine learning and artificial intelligence approaches

Identifying signatures of viral adaptation, improving prediction of evolutionary trends, and integrating multiple data types for enhanced surveillance

Gaining advanced training in the use of bioinformatics platforms, phylogenetic and phylodynamic modeling, and modern machine learning frameworks

Increasing knowledge in areas that align with the WRAIR mission of advancing pathogen genomics and surveillance

Qualification

GenomicsBioinformaticsComputational BiologyMachine LearningPythonRUnix/LinuxHigh-Performance ComputingNext-Generation SequencingPhylogenetic MethodsPhylodynamic MethodsIndependent ResearchCommunication Skills

Required

An earned Ph.D in one of the eligible disciplines

Degree must have been received within five years of appointment start date

Preferred

Academic coursework or research experience in genomics, bioinformatics, or computational biology

Extensive experience with Unix/Linux environments for managing and analyzing large-scale genomic data

Strong capability in programming languages commonly used in bioinformatics, including Python and R, for data analysis, statistical modeling, and visualization

Familiarity with high-performance computing (HPC) systems for large-scale data processing, parallelized workflows, and computationally intensive analyses

Demonstrated experience applying phylogenetic and phylodynamic methods to viral sequence data

Exposure to machine learning or artificial intelligence methods, particularly as applied to genomics or infectious disease data

Experience in next-generation sequencing (NGS) data analysis, including quality control, assembly, alignment, and variant detection

Evidence of independent research experience at the postdoctoral level, with a track record of scholarly publications or presentations in viral genomics, bioinformatics, or computational biology

Strong communication skills for effective collaboration in an interdisciplinary research environment