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Scientist : Discovery Sciences

Job in Alameda, Alameda County, California, 94501, USA
Listing for: iQ Biosciences
Full Time position
Listed on 2026-09-26
Job specializations:
  • Research/Development
    Research Scientist, Immunology Research, Drug Discovery, Biotech Research
Salary/Wage Range or Industry Benchmark: 90000 - 120000 USD Yearly USD 90000.00 120000.00 YEAR
Job Description & How to Apply Below
Position: Scientist I: Discovery Sciences

About iQ Biosciences

iQ Biosciences is a contract research organization dedicated to providing immunology research bioservices, biospecimens, and bioconjugation enabling preclinical research studies. We serve as a trusted partner for the biomedical community and help deliver innovative therapeutics for physicians and patients. iQ Biosciences fosters a company culture of employee inclusion, accountability, integrity, and a shared sense of team urgency, knowing that patients are waiting with critical needs.

We are entering a dynamic growth phase and are seeking a highly motivated Scientist I to join our Discovery Sciences group. This position offers high growth potential, as the company continues to establish a strong team, and provides a great learning opportunity to encounter the different approaches that drug development companies, from start-ups to big pharma, are taking to improve human health in the immunology and oncology therapeutic areas.

Position Overview:

Scientist I – Discovery Sciences

The successful candidate will be primarily responsible for the design and execution of therapeutic antibody or small molecule immunoassays, cell-based assays, and analyte quantitation for research, preclinical, and early drug development projects. This role requires solid knowledge of cellular immunology, immuno‑oncology, therapeutics of various modalities (i.e. small molecule, biologics, antibody conjugates, cell‑based (CAR‑T), etc.), along with associated lab skills (i.e. flow cytometry, tissue culture, cell‑based assays, etc.).

As a CRO, we operate in a fast‑paced, highly collaborative environment. After an initial training period, the Scientist I is expected to work independently, rapidly adapt to shifting priorities, and confidently execute and interpret assay results. You will manage multiple client projects concurrently, coordinate with internal teams, and communicate directly with clients.

The person who thrives at iQ is a hands‑on, delivery‑oriented immunologist who is comfortable owning a project end‑to‑end. Whether working from a complete SOW or navigating ambiguity, they communicate with clarity and confidence internally and externally, find the breadth of therapeutic exposure energizing rather than distracting, hold themselves accountable for timelines as a matter of professional pride, and know their data directly informs patient therapeutic decisions.

Responsibilities:
Project Execution & Study Management:
  • Design, plan, and execute experiments for client projects and internal R&D under general guidance.
  • Proactively manage day‑to‑day study logistics, including reagent preparation/ordering, experimental execution, data analysis, and preparation of summaries.
  • Provide timely updates to internal stakeholders and adapt to evolving project needs.
Assay Development & Laboratory Work:
  • Perform in vitro, ex vivo, and cell‑based assays (e.g., cytotoxicity assays, ELISAs, reporter assays) to support functional characterization of therapeutics.
  • Perform multi‑color flow cytometry experiments, including panel design, sample preparation, staining, data acquisition, and analysis.
  • Support development and optimization of new or existing assays as needed.
Data Analysis & Reporting:
  • Analyze and interpret experimental data with attention to detail and scientific accuracy. Prepare clear data summaries and contribute to drafting study reports, presentations, and client deliverables. Maintain accurate and organized experimental records.
  • Utilize internal tools and assist in the onboarding of emerging technologies (including AI‑enabled tools, as available) to support data analysis, visualization, and reporting efficiency.
Troubleshooting & Scientific Learning:
  • Troubleshoot experimental challenges by reviewing data,…
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