DotJcoM LTD
DotJcoM LTD
Tunisie

102 Post-Operation Follow-Up App PFE

Mobile Development (Flutter)Healthcare ITAI / Machine Learning

Publié il y a 7 mois

Stage
⏱️4-6 mois
💼Hybride
📅Expiré il y a 6 mois
Reste lisible (ATS friendly).

Description du poste

Project overview

  • Mobile application to connect doctors and patients for post-surgery monitoring.
  • Focus on continuous care: tracks recovery progress, medication reminders and multiple health parameters.

Key features

  • AI-driven detection of abnormal recovery patterns with instant alerts to healthcare providers.
  • Secure patient–doctor communication channel and access to personalized advice.

Technical stack & required skills

  • Required technologies: Flutter (mobile frontend), Firebase (real-time DB/auth/notifications), Node.js (backend/API).
  • Expected skills: mobile UI implementation, REST/Realtime API integration, authentication, push notifications, basic ML/AI integration or interfacing with ML services.

Responsibilities & tasks

  • Implement and polish the Flutter mobile client (UI, forms for vitals, medication reminders).
  • Integrate Firebase services (authentication, realtime database / Firestore, push notifications) and connect to a Node.js backend for business logic and alerts.
  • Implement or integrate AI module to analyze health parameter streams and raise alerts for abnormal patterns.
  • Ensure secure communication and privacy best practices for patient data.

Expected deliverables

  • Functional Flutter app for patients and a simple provider interface/flows for doctors.
  • Backend Node.js services and Firebase configuration supporting authentication, data storage, notifications and AI-alert pipeline.
  • Documentation: setup, architecture overview, and testing notes; demo showing monitoring, reminders and alerting flows.

Duration & trainees

  • Duration: 4-6 months.
  • Number of trainees: 1 PFE.

How to apply

  • Apply using the project form: Apply here
  • In your application, highlight relevant Flutter projects, backend experience (Node.js/Firebase) and any exposure to ML/AI for anomaly detection.