I am looking for an experienced academic researcher to develop a full SCI / SCI-Expanded (preferably Q1) level research paper from scratch. The topic can be broadly framed around: “The Impact of AI-Assisted Coding Tools on Software Developer Productivity, Code Quality, Cognitive Load, and Engineering Processes” …but I am open to alternative angles as long as they are technically rigorous, novel, and suitable for a Q1 journal. I am also flexible regarding data sources and research design. You may propose: Empirical datasets (GitHub, GitLab, StackOverflow, PR logs, CI/CD pipeline metrics, Copilot telemetry-style datasets). Controlled experiments with developers (time-to-task, error rates, acceptance levels). Mining software repositories (MSR). Multi-metric productivity models (SPACE, DORA, code quality metrics). Industry-level datasets (NOT low-quality or irrelevant regional datasets). However, I am NOT interested in: Low-quality local datasets (e.g., a small district, single classroom, or hobby developer samples). Purely theoretical / literature-review-only papers. AI-generated content without academically valid methodology. The final paper must be: Original, plagiarism-free, and suitable for SCI or SCI-Q1 submission 100% supported with real, verifiable data Written in a high-quality academic tone Structured according to top-tier journals (abstract, intro, RQs, methodology, results, discussion, conclusion, limitations, references) Aligned with rigorous scientific methodology (validity, reliability, IRB considerations if needed) Fully formatted according to a journal template (Springer, Elsevier, IEEE, MDPI, etc.) Expected Deliverables: Full research paper (7,000–10,000+ words) Dataset + data collection explanation All statistical analyses (regression, ANOVA, ML models, etc. depending on design) Graphs, tables, code repository (if applicable) A short list of recommended journals for submission Required Qualifications: Proven track record of SCI or Q1 publications Strong knowledge in software engineering, empirical methods, AI/ML, and developer productivity research Ability to design a realistic and high-quality data-driven study Strong statistical background Excellent academic English writing skills Bonus if you have experience in: GitHub Copilot / AI-assisted coding tools Mining Software Repositories (MSR) Developer productivity frameworks (SPACE, DORA) Experimental design with human subjects If you have the skills to produce a journal-ready, publication-quality, data-backed scientific paper, feel free to submit: Your CV / Google Scholar profile Examples of previous SCI or Q1 publications A short proposal (1–2 paragraphs) describing the recommended direction and dataset Looking forward to working with a talented researcher who can deliver at top academic standards.