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Thomas Jefferson University

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Postdoctoral Position in Computational Biology and RNA Decay at Thomas Jefferson University Thomas Jefferson University in United States

Degree Level

Postdoc

Field of study

Biochemistry

Funding

Available

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Country

United States

University

Thomas Jefferson University

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Keywords

Biochemistry
Computer Science
Molecular Biology
Biomedical Engineering
Biology
Computational Biology
Neuropsychology
Next-generation Sequencing
Rna-seq
Neurodegenerative Disease
Genomic
Bioinformatic

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About this position

A postdoctoral computational biologist position is available in the laboratory of Dr. Fadia Ibrahim in the Department of Biochemistry and Molecular Biology at Thomas Jefferson University.

The project focuses on the molecular mechanism of a novel co-translational RNA decay process called ribothrypsis and on understanding how RNA dysregulation contributes to neurodegenerative diseases. The successful candidate will join a research program that brings together molecular biology, biochemistry, RNA sequencing technologies, and advanced computational analysis.

The postdoctoral researcher will support ongoing projects by developing and implementing bioinformatics tools and pipelines and by overseeing the processing, management, and analysis of next-generation sequencing data. The work emphasizes computational investigation of RNA-focused datasets and the integration of experimental and computational approaches in a multidisciplinary environment.

The role is based in Philadelphia within a university setting that combines biomedical research, medical education, and translational science.

Funding details

Available

What's required

Ph.D. in Computational Biology, Bioinformatics, Computational Sciences, or a related discipline is required. Applicants should have proficiency in R and Python, experience working in Linux/Unix environments with command-line bioinformatics tools, and experience analyzing and interpreting NGS data including RNA-Seq and Ribo-Seq. Required expertise includes data evaluation and visualization such as differential expression, ribosome occupancy, poly(A) tail analysis, and modification detection. Candidates should also have basic knowledge of molecular biology techniques, familiarity with biological data, knowledge of statistical methods applied to biological datasets, strong analytical/problem-solving/quantitative skills, the ability to collaborate in a multidisciplinary team, and a publication track record in relevant fields. Preferred qualifications include familiarity with Illumina and Oxford Nanopore Technologies, experience integrating and analyzing large-scale biological datasets, use of ENCODE, UCSC Genome Browser, Ensembl, Bioconductor, and NCBI databases, experience managing computational servers and data storage/backup, ability to formulate scientific hypotheses, and strong organizational, written, and verbal communication skills.

How to apply

Submit a single PDF containing your CV, a cover letter describing your research experience and interests, and the contact details of three referees. Apply through the provided Workday application link.

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