Provisioned for the Johns Hopkins Internship Academies cohort. Do not redistribute.
Bionectech & the Intern Academy
Good morning.
Hours logged
0.0
of 100 hours minimum
Modules complete
0/10
begin with Module 1
Average score
—
engine-attested
Next Teams call
—
every 10 days
The Ten Modules
Read · Lab · Knowledge check · Reflection
The Case Builder
Open after Module 1
The capstone of this internship is your case portfolio. Author a patient vignette, identify the root cause from the WHO five dimensions, propose an intervention from the five evidence-based protocols, and the engine will analyse what you flagged and what you missed. Cases accrue toward your final presentation in Module 10.
House Rules
A short charter
The internship charter
You are joining a healthcare-AI team, not a coding bootcamp. The work you do here will feed real product decisions. We hold three things sacred: (i) patient data privacy — you will never see real PHI; (ii) intellectual honesty — your reflections are graded for thinking, not for telling us what we want to hear; (iii) the appended ledger — every score and every case you submit is hash-chained and timestamped so your work is permanent and tamper-evident.
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Knowledge Check
Five questions. The engine grades immediately. You may try once; your first answer is recorded.
Reflection
0 wordsSaved —
Capstone Workshop
Case Builder
Where you put theory through its paces.
How it works
Author a synthetic patient (no real PHI). Tick every flag the case genuinely contains. Pick a root cause. Pick an intervention. The engine then runs a co-firing analysis against the evidence base: it tells you which clinical issues you correctly identified, which you missed (logical errors), and how strongly your chosen intervention matches the case's actual root cause. There is no right answer the first time; iteration is the point.
Patient Vignette (synthetic only)
Flags Observed in This Case
Tick every flag that genuinely applies based on the narrative above. The engine compares your flag set against logical co-firing pairs.
Root Cause & Intervention
Your Portfolio
Internship Ledger
Your Hours
Tamper-evident, hash-chained, append-only.
Total logged
0.0
hours
From modules
0.0
automatic
Off-platform
0.0
readings, calls, drafting
Target window
100–150
10 weeks × 10–15 hrs
Log Off-Platform Hours
Readings, Teams calls, drafting, advisor meetings
Ledger
append-only · SHA-256 chained
Timestamp
Type
Detail
Hours
Chain hash
Export for Supervisor
Ahead of the 10-day Teams call
Click below to download a signed copy of your ledger (hours, module progress, cases, chain head). Email or hand it to your supervisor before the Teams call so they can review your work in the Supervisor view.
Cohort Supervision · Supervisor Mode
The Two of Them
Read-only visibility into the cohort's progress.
How this works
Each student exports a signed ledger from their Hours view ahead of the 10-day Teams call. The supervisor pastes the export below; the engine verifies the SHA-256 chain hash; the student's work appears in the roster. No real-time sync — that is by design. The 10-day cadence is the supervision rhythm. This view is accessible to both the founder (Bionectech) and the JHU Life Design Lab.
Students imported
0
of 2 in the cohort
Cohort hours
0.0
across all imports
Modules complete
0
of 20 total (10 × 2)
Cases authored
0
capstone minimum 5 each
Roster
Click a row to drill in
Import a Student Ledger
JSON from student's "Export my ledger"
Paste the contents of the JSON file the student exported. The engine will verify the chain hash and store the import locally. Re-importing overwrites the prior copy for that student.