Canada
Question Answering, Information Retrieval, Semantic Search, Generative AI, Retrieval Augmented Generation (RAG)
Question Answering, Information Retrieval, Semantic Search
-Analyze multivariate data and perform statistical tests on multimodal brain images -Fuse multimodal medical images (PET/fMRI/DTI) and prepare them for machine learning algorithms -Implement and test multimodal machine learning algorithms for classification of healthy controls and (Schizophrenia/Tourette) patients -Visualize data in high dimensionality -Develop a multimodal data coregistration pipeline -Participate in the elaboration of 2 abstracts for the 6th Resting State and Brain Connectivity Conference
-Design, implement and test a new ecommerce/recommendation machine learning model using Apache Spark -Benchmark multiple machine learning/data mining algorithms such as ALS (Alternating Least Squares), LSH (Locality Sensitive Hashing), FP-Growth (Frequent Pattern Growth) and test their scalability -Code a REST API to serve the recommendation model in a demo environment and deploy the model -Perform big data (millions of entries) preparation and analysis for machine learning algorithms -Develop a recommendation model evaluation framework and identify relevant metrics
-Assist the students in understanding the practical work of the course GTI310 - Multimedia data structures -Evaluate the practical work of software development delivered by the students -Have excellent knowledge of the different data structures and algorithms of compression, search and sorting -Have excellent knowledge of the different representations of multimedia data
-Develop and maintain features for a distributed analytics Java backend accepting millions of events -Integrate StatsD metrics for requests monitoring -Develop unit and functional tests -Use multiple AWS services such as DynamoDB and Kinesis Streams