CAMI Project – Research Intern – Smart Schedule Management
@Laboratorul AIMAS, UPB, în Splaiul Independentei nr. 313 Sector 6, Bucureşti, 060042

Responsabilități

CAMI (Artificially intelligent ecosystem for self-management and sustainable quality of life in Ambient Assisted Living) [1] is a European AAL (Ambient Assisted Living) project managed by UPB.
CAMI offers an integrated AAL solution by providing services for health management, home management and well-being.
In CAMI, part of the envisioned care for elderly users involves setting up a schedule of medication intake reminders, physical exercises that can be done indoors (exergames), as well as the tracking of daily activities of an end user (e.g. cooking, eating, lying on the couch, sleeping).
However, a greater level of dynamicity is expected for the daily life of a senior citizen (e.g. ignore medication reminder, postpone physical exercise sessions given inconvenient mood, forget to perform a health measurement, too sedentary/active periods).

You will be involved in the task of developing a service for smart scheduling and rescheduling of elderly user activities, taking into account the dynamics explained above.
You will handle aspects such as:

  • Set up scripts generating scenarios of daily, weekly and monthly end-user activities
  • Set up scripts simulating various user behavior for acknowledging, postponing of existing events and definition of new ones
  • Semantic modeling of activity context (e.g. what the user was doing when ignoring/postponing reminder)
  • Design and implement a (re)scheduling algorithm that addresses the simulated user behavior and takes into account user preferences (e.g. no physical activities after 4pm)

You will be mentored and guided in your scenario design and development efforts by researchers from the AI-MAS laboratory [2] who are members of the CAMI project.

[1] http://www.camiproject.eu/

[2] http://aimas.cs.pub.ro/

Calificări

  • Currently pursuing a BA or MSc degree in Computer Science or related technical field
  • Having a proactive approach to problem solving
  • Good knowledge of one or more general purpose programming languages including but not limited to: Java, Python, C#
  • Experience in AI domains involving: semantic data representation (e.g. ontologies), planning and/or rule-based systems is a plus
  • Demonstrated extra curricular activities & projects is a plus

Beneficii

  • Good compensation package
  • Flexible schedule (work from home allowed)
  • Office located in PRECIS building of UPB
  • Chance to be involved in further national and european projects managed by UPB
  • Support towards writing an academic paper based on obtained results

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