Associate Researcher I- Pharmacological Sciences

The project focuses on the generation, processing, and interpretation of high‑throughput omics datasets to understand molecular mechanisms underlying biological phenotypes. This includes integration of genomics, transcriptomics, proteomics, and/or metabolomics data to identify biomarkers, regulatory pathways, and functional networks. The research aims to support hypothesis‑driven discovery as well as data‑driven modeling using computational and statistical approaches. 

• Perform data preprocessing and quality control for omics datasets (e.g., FASTQ QC, adapter trimming, alignment, quantification).
• Conduct bioinformatics analyses such as differential expression, pathway enrichment, clustering, and network analysis.
• Use established pipelines and tools.
• Maintain and update data management systems, ensuring proper documentation, version control, and reproducibility.
• Assist with sample preparation protocols when needed (RNA extraction, library prep, protein isolation, mass‑spec sample prep).
• Generate figures, reports, and visualizations for internal meetings, manuscripts, and presentations.
• Collaborate with senior researchers to interpret results and refine analytical strategies.
• Follow laboratory safety procedures and institutional guidelines.

Goals/Outcomes of the Research Project: 

• Produce high‑quality, reproducible omics analyses that advance the project’s scientific aims.
• Identify key molecular signatures, pathways, or biomarkers relevant to the biological question.
• Contribute to manuscripts, presentations, and grant applications through data analysis and visualization.
• Develop and refine computational pipelines that can be reused by the research team.
• Support the generation of new hypotheses and experimental directions based on data‑driven insights.
• Build a robust, well‑documented dataset and analysis framework that supports long‑term research continuity.

• Bachelors or Masters degree in science or related field required
• No experience required. One year of research experience preferred.

 

Preferred Skills

• Bachelor’s or Master’s degree in Bioinformatics, Computational Biology, Molecular Biology, Genetics, Biostatistics, or a related field.
• Foundational understanding of molecular biology and high‑throughput sequencing technologies.
• Proficiency in R and/or Python for data analysis.
• Familiarity with Linux/Unix environments.
• Strong organizational skills and ability to maintain detailed laboratory and computational records.
• Ability to work independently while contributing to a collaborative research environment.

 

Experience Preferred:

• Prior experience with omics datasets (bulk or sc-RNA‑seq, whole‑genome sequencing, ATAC seq or ChiP-seq, proteomics, or metabolomics).
• Hands‑on experience with at least one major analysis pipeline (e.g., differential expression, variant calling, clustering).
• Experience generating publication‑quality plots and figures.
• Experience with machine learning, cloud computing, or workflow automation.
• Experience with wet‑lab protocols relevant to sample preparation.

 

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About the Mount Sinai Health System:

Mount Sinai Health System is one of the largest academic medical systems in the New York metro area, with more than 48,000 employees working across eight hospitals, more than 400 outpatient practices, more than 300 labs