AI-Powered Acne Lesion Progression Simulator - AB-095

Genre de projet: Recherche
Discipline(s) souhaitée(s): Biochimie / biologie moléculaire, Sciences de la vie, Médecine, Microbiologie / immunologie
Entreprise: Faculty of Skin
Durée du projet: 6 mois à 1 an
Date souhaitée de début: Dès que possible
Langue exigée: Anglais
Emplacement(s): AB, Canada
Nombre de postes: 1-2
Niveau de scolarité désiré: Études de premier cycle/baccalauréatMaîtriseDoctoratRecherche postdoctoraleNouvelle diplômée/nouveau diplômé
Ouvert aux candidatures de personnes inscrites à un établissement à l’extérieur du Canada: No

Au sujet de l’entreprise: 

Faculty of Skin is a Canadian AI-health startup focused on personalizing skincare and democratizing dermatologic insights. Through advanced machine learning, Faculty of Skin develops digital tools to help patients, primary care physicians, and cosmetic companies make informed treatment decisions. Our mission is to bridge the gap between consumer wellness, dermatology, and evidence-based AI. We work across spa and clinical environments and specialize in building explainable and interoperable software.

Veuillez décrire le projet.: 

This project will develop technology to forecast how acne lesions progress over 90 days, using longitudinal lifestyle, skin and treatment data. The goal is to provide an evidence-based tool that predicts the effects of various treatment and behavioral interventions on acne outcomes.

The project will have two major components:
Modeling: Build and train an RNN model using curated inputs including baseline lesion counts, treatment regimen, and lifestyle factors such as sleep, diet, and stress.
Data Collection Study: Design and support a longitudinal data collection study that gathers daily or weekly skin health data from participants over a 90-day period. This data will power the initial training of the simulation engine.

Expertise ou compétences exigées: 

- Background in dermatology, medical education, or clinical research
- Strong understanding of acne, lesion classification, and treatment mechanisms
- Experience or willingness to support the design of a 90-day longitudinal skin tracking study
- Ability to help define clinically meaningful inputs and outputs for an acne simulation model
- Familiarity with common acne treatments and how their efficacy varies based on patient characteristics