Associate Research Scientist

This role supports discovery research across metabolic and liver‑focused programs by driving hands‑on execution of complex in‑vitro cell models and a broad suite of molecular, biochemical, and imaging‑based assays. The scientist will work extensively with advanced mammalian systems, including iPSC‑derived tissues, organoids, and primary/3D cultures, and will generate high‑quality experimental data to evaluate gene targets and therapeutic candidates.

Core responsibilities include maintaining long‑term, high‑complexity cell cultures; performing RNA‑based assays (RT‑qPCR, ddPCR), ELISAs, Western blotting (manual or automated), functional/metabolic readouts, and high‑content or confocal imaging. The scientist will contribute to assay development, optimization, and troubleshooting while supporting opportunities to scale assays into higher‑throughput or automation‑enabled workflows. Strong documentation practices (SOPs, ELN) and clear communication of experimental design and conclusions are essential.

Key Competencies

• Advanced mammalian cell culture expertise, including iPSC‑derived, primary, 3D, and long‑term systems.
• Proficiency with molecular and biochemical assays, such as RT‑qPCR, ddPCR, ELISA‑type assays, Western blotting (manual and/or automated), metabolic and functional readouts.
• Experience with imaging‑based methods, including immunofluorescence, high‑content imaging, confocal microscopy, and quantitative image analysis.
• Ability to develop, optimize, and troubleshoot assays for target characterization and therapeutic evaluation, with a data‑driven approach to improving workflows.
• Familiarity with automation platforms (e.g., Hamilton, Agilent) and high‑throughput screening concepts.
• Meticulous laboratory technique, strong bench precision, and reliable execution of complex assays.
• Clear, GLP‑aligned documentation, including SOP authorship and comprehensive ELN practices.
• Strong communication skills to articulate experimental strategy, observations, data quality, and technical decisions.
• Adaptability to dynamic research priorities and versatility to support multiple discovery programs.