Artificial Intelligence & Machine Learning Application

Our research institute explores the root causes of global problems and publish reports on critical issues in relation to the UN SDG's. We want to leverage the latest technology to advance our capacity. Applications of this technology include LLM's, RAG, recommendation algorithms, predictive analytics / forecasting like lifetime values, modelling and classifications. We would like to collaborate with students to apply the latest artificial intelligence (AI) and machine learning (ML) techniques to our existing dataset. Students will develop an AI / ML model related to any of the aforementioned applications. This will involve several different steps for the students, including: Conducting background research on our existing products and the dataset. Analyzing our current dataset. Researching the latest AI / ML techniques and how they could be applied to our data. Developing an AI / ML model that provides unique outcomes or insights into our data. Providing multiple solutions that can be applied to solve the same problem.

Literature Summary Research Assistant

Our research institute publishes dozens of papers every year to promote projects in our field of research. Among these papers are systematic reviews of relevant literature, which analyze the progression of research within our field or problems within a specific vertical of the UN SDG's. We would like to collaborate with students to support our literature review process by categorizing papers, summarizing important findings and fact checking. Bonus points if you can develop a software program or workflow that helps execute this at scale. This allows us to extract and process data more easily. This will involve several different steps for the students, including: Familiarizing themselves with our research and the types of academic papers that we are interested in. Reading studies relevant to our area of research. Applying the categorization scheme to classify relevant studies. Summarizing important results from relevant studies. Bonus steps in the process would also include: Working with researchers to draft a publication based on the results.

Software Development: MERN Stack Web Application

Team SME at Thought Experiment Labs helps Canadian small to medium sized business owners increase their revenue, boost profitability and modernize operations in the digital age. The main goal for the project is to build a web application using the MERN stack that will help small to medium sized businesses find new opportunities, grow their operations, modernize, boost profitability, and increase revenue. The application should adhere to industry standard software engineering principles. This will involve several different steps for the learners, including: - Understanding the requirements and goals of Thought Experiment Labs, Team SME and other details - Designing the architecture of the web application using the MERN stack. - Developing the front-end and back-end of the web application. - Testing and debugging the web application to ensure it meets industry standards. - Deploying the web application and providing documentation for future maintenance.

Artificial Intelligence & Machine Learning Application

Thought Experiment Labs wants to leverage the latest technology to better serve their clients, guide strategic decision making and maximize the value we add to the market. Applications of artificial intelligence include recommendation algorithms, predictive analytics like lifetime values, fraud detections, and classifications. We would like to collaborate with students to apply the latest artificial intelligence (AI) and machine learning (ML) techniques to mountains of data, from a wide variety of data sources. Students will develop an AI / ML model related to any of the aforementioned applications. This will involve several different steps for the students, including: Conducting background research on our existing products and the dataset. Analyzing our current dataset. Researching the latest AI / ML techniques and how they could be applied to our data. Developing an AI / ML model that provides unique outcomes or insights into our data. Providing multiple solutions that can be applied to solve the same problem.