The Pre-Fellowship Track is a structured preparation pathway for applicants who are not yet ready for the Global NanoTRIZ Fellowship. It helps you build a verifiable “Readiness Package” through milestone-driven work, supervised feedback, and ethical AI workflows. Completion of Pre-Fellowship does not guarantee Fellowship admission—it produces the artifacts needed for merit-based evaluation.

 

Who this is for

Choose Pre-Fellowship if you:

• have limited or no research portfolio (no public artifacts, no reproducible work)

• have interest but no clear topic, research question, or plan

• need foundations in research methods, literature synthesis, analysis, or scientific writing

• want a structured way to demonstrate readiness before applying to the Fellowship

 

Roles you can join (clear pathways)

Applicants enter Pre-Fellowship in one of the roles below. Each role has specific milestones and measurable outputs.

1. Pre-Fellowship Candidate (Readiness Builder)
   Build a complete Readiness Package for merit selection.

2. Project Starter (Scope & Roadmap)
   Turn an initial interest into a defined research question, roadmap, and first deliverables.

3. Research Skills Builder (Methods & Evidence)
   Strengthen core research capabilities: sourcing, critical evaluation, methods, reproducibility, uncertainty.

4. Portfolio Builder (Admissions-Ready Artifacts)
   Produce public, verifiable outputs (write-ups, posters, OSF/GitHub artifacts) suitable for applications.

5. Ethical AI Workflow Trainee (Responsible Research Acceleration)
   Learn ethical AI use with verification, attribution, and disclosure logs—no black-box writing.

6. Division Explorer (Track Selection)
   Complete short test-deliverables across divisions to select the best-fit research track.

 

What you will produce (measurable outputs)

All Pre-Fellowship participants work toward a Readiness Package that can be reviewed and verified.

Required Readiness Package (minimum)

1. Research Brief (1 page)
   Problem → research question → assumptions → method → milestones → risks.

2. Literature Map (30–50 sources)
   Structured bibliography + topic clustering + “what is known / unknown” + gap statement.

3. Reproducible Artifact (OSF or GitHub)
   Repository or OSF project with README, setup steps, and reproducible results/protocols.

4. Mini-Output (2–4 pages)
   Short technical report, mini-review, poster draft, or preprint draft outline (as appropriate).

5. Ethical AI Use Log
   Clear disclosure of AI assistance: where used, how verified, and how sources were handled.

 

Optional (strong signals for readiness)

• baseline replication with limitations (methods + results + comparison to credible reference)

• small dataset/analysis pipeline with documented evaluation metrics

• figure set (clean visuals) + references + limitations section

• short recorded presentation (3–5 minutes) explaining the work and its boundaries

 

Program format

• Milestone-driven: weekly deliverables and structured feedback

• Supervised: review by a mentor/coach; escalation to a supervisor when available

• Evidence-first: claims must be traceable to sources, data, or reproducible methods

• Ethical AI: AI is allowed for acceleration (mapping, drafting support, organization), but verification and ownership remain with the Fellow

 

Entry requirements (simple and practical)

To start Pre-Fellowship, you submit:

• a short statement of goals (what you want to achieve in 6–12 months)

• current level (high school / university / PhD / professional)

• any existing links (optional but encouraged): GitHub/OSF/arXiv/portfolio

• time commitment estimate (hours per week)

• declaration of ethical conduct and original work (with proper citation)

No prior publications are required.

 

Typical duration

• 4–8 weeks (recommended) for a full Readiness Package

• 2–4 weeks (intensive sprint) for focused applicants who can commit more time

 

Completion criteria (what “finished” means)

You are considered Pre-Fellowship Completed when you have:

• all required Readiness Package components submitted

• a verifiable link set (OSF/GitHub + document outputs)

• documented verification steps and an Ethical AI Use Log

• a clear next-step plan (Fellowship application or continued preparation)

 

How Pre-Fellowship connects to Fellowship (merit-based)

Pre-Fellowship produces the evidence used for selection. After completion, you may apply to the Fellowship with:

• Readiness Package links (required)

• top 5 skills + evidence links (required)

• a 1-page project proposal (problem, method, milestones, risks)

• resources and constraints (tools, equipment access, datasets, time)

 

Possible decision outcomes:

• Not yet ready (specific gaps + next steps)

• Eligible to apply (minimum evidence achieved)

• Shortlisted (strong fit; interview/review stage)

• Accepted (matched to a supervisor when available)

 

What Pre-Fellowship is not

• not an accredited degree program

• not a publication guarantee or admissions guarantee

• not ghostwriting or “paper for sale”

• not clinical training or medical advice (for health-related topics)