Large Language Model innovation for Agri-Food sector applications - ON-956

Genre de projet: Recherche
Discipline(s) souhaitée(s): Génie - informatique / électrique, Génie, Informatique, Sciences mathématiques
Entreprise: Anonymous
Durée du projet: 4 à 6 mois
Date souhaitée de début: Dès que possible
Langue exigée: Anglais
Emplacement(s): Stoney Creek, ON, Canada; Halifax, NS, Canada; Toronto, ON, Canada
Nombre de postes: 1
Niveau de scolarité désiré: Recherche postdoctoraleNouvelle diplômée/nouveau diplômé
Ouvert aux candidatures de personnes inscrites à un établissement à l’extérieur du Canada: Yes

Au sujet de l’entreprise: 

A multinational food technology company with headquarters in Stoney Creek, Ontraio. The company provides AI powered technology for companies across the food and agriculture supply chain.

Veuillez décrire le projet.: 

This project is dedicated to the design and implementation of advanced neural network architectures with the goal of developing state-of-the-art Large Language Models (LLMs). Key project goals include:

1. Neural Architecture Development: Crafting and implementing cutting-edge neural network architectures to underpin the next generation of LLMs, with a focus on efficiency, adaptability, and performance.
2. Dataset Management: Curating and managing extensive, high-quality datasets for LLM training, prioritizing diversity and privacy, ensuring the models are well-rounded and ethically sound.
3. Performance Benchmarking: Establishing comprehensive benchmarks and testing protocols to rigorously evaluate the models' performance across various metrics and identify opportunities for enhancement.
4. Model Integration: Seamlessly integrating LLMs into a range of applications, optimizing for efficient deployment and scalability within the Food & Agriculture sector's technological ecosystem.
5. Customization for Agri-Food Tasks: Utilizing techniques such as transfer learning and fine-tuning to customize LLMs for specific tasks relevant to the Food & Agriculture sector, thereby increasing the practical value of the models.

Expertise ou compétences exigées: 

Large Language Models, Machine Learning, Computer Science