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Computational Biology Post Doctorate Fellow, Biomarker Department
Job in
Carlsbad, Tom Green County, Texas, 76934, USA
Listed on 2026-02-23
Listing for:
Scorpion Therapeutics
Full Time
position Listed on 2026-02-23
Job specializations:
-
Research/Development
Research Scientist, Data Scientist
Job Description & How to Apply Below
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Role SummaryComputational Biology Post Doctorate Fellow in the Biomarker Department. Join the Biomarker group to develop, support, and implement the biomarker strategy for Ionis’ pipeline, focusing on proteomic and EEG data to identify biomarkers for neurology programs. Responsibilities include aggregating and harmonizing datasets, building analysis pipelines in R and Python, and validating findings in cohorts and targeted assays. Strong computational biology background and experience with multimodal omics data are required;
excellent cross‑functional communication is essential.
- Access, harmonize, and analyze proteomics and EEG data in collaboration with the Biomarker group and external partners
- Independently design and deploy computational pipelines to process and analyze proteomics and EEG data
- Communicate project status, timelines, and analysis updates effectively with team members
- Integrate findings from omics datasets to support Ionis programs
- Participate in collaborations to access and contribute to additional datasets for related projects
- Required:
PhD in computational biology or a related field - Preferred:
Degree and/or background in neurological diseases and/or biomarker discovery; experience handling EEG data - Required:
Critical‑thinking and problem‑solving skills with attention to detail - Required:
Experience designing and executing scientific experiments and projects - Required:
Experience working with multi‑modal omics datasets and large proteomic datasets (e.g., O‑link, untargeted LC‑MS data), evidenced by high‑impact publications - Required:
Proficiency in R, Python, or similar languages for analysis of processed proteomics data, including data wrangling, QC, normalization, and differential protein abundance testing - Preferred:
Experience with tidyverse, MSstats, DEP2, pandas, numpy, scikit‑learn, and pathway/network analysis tools (e.g., GSEA/fgsea, cluster
Profiler) - Beneficial but not essential:
Running targeted protein ELISAs to validate computational findings
- PhD in computational biology or a closely related field
- Candidate must be in San Diego or willing to relocate (onsite or hybrid)
- Travel minimal 0–10%
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