Service Details
Applied experiment design and proposal support that connects scientific rigor, clear methods, and practical workflows to produce defensible, review-ready submissions.
Experiment Design, Methods, and Proposal Support
I help plan experiments with clear objectives, strong methods, and practical sampling timelines so studies are defensible from the start. I support scientific writing for proposals and grants, including rationale, methodology, expected outcomes, and structure that reviewers can follow. My work is grounded in postharvest physiology, data analysis in R and Python, NIR sensing projects, and computer vision workflows.
What I help with
Scope and requirements
Experimental design with clear objectives, treatments, controls, and response variables.
Design and methods draft
Sampling plans with practical timepoints, replication strategy, and logistics.
Methods writing
Methods writing for proposal sections that are specific, concise, and reproducible.
Workflow diagrams
Workflow diagrams that communicate study flow and decision points.
Service overview
I support graduate students, research labs, and applied project teams with rigorous, practical proposal development. The focus is scientific clarity, realistic execution, and methods that align with reviewer expectations. As a PhD student in Horticulture and Postharvest Biology at the University of Georgia, I bring domain experience in postharvest physiology, peach chilling injury, sensor-based workflows, and computational analysis.
Deliverables
- Study design table with treatments, replicates, timepoints, and variables.
- Methods draft tailored to your call format and scientific scope.
- Analysis plan outline with expected outputs and interpretation flow.
- Figure and table placeholders for proposal clarity and consistency.
- Reviewer-focused checklist for completeness and internal quality control.
- Final polished proposal section package for submission assembly.
Best fit for
- Graduate students preparing grant, fellowship, or thesis-related submissions.
- Research labs building structured methods for funded project proposals.
- Extension projects requiring clear study logic and practical outcomes.
- Agri-tech pilots that need defensible trial design before deployment.
- Postharvest trials in fruit quality, storage, and chilling injury studies.
- Sensor and machine learning projects, including NIR, YOLO, and CNN workflows.