D. in biological oceanography, marine ecology, oceanography, ecology, environmental science, or a related field; Experience working on plankton ecology and pelagic ecosystem dynamics (preferred); Strong quantitative and analytical skills, with preference for experience in coupled physical-biological modeling, statistical analyses, and/or machine-learning approaches; Experience working with ecological or oceanographic datasets is preferred; Proficiency in scientific programming and data analysis (e.g., R, Python, MATLAB); A demonstrated record of peer-reviewed scientific publication; and. Responsibilities may include: Analysis and synthesis of long-term plankton and oceanographic datasets from observational programs and model outputs; Development of statistical and machine-learning approaches (e.g., GAMs, Random Forests, synchrony analyses); Investigation of plankton population dynamics and trophic transfer; Participation in coupled physical-biological modeling and connectivity analyses; Preparation of peer-reviewed publications and conference presentations; Contributing to proposal development and collaborative research initiatives involving federal agencies, regional research programs, and academic partners.