AI & Machine Learning

Artificial intelligence and machine learning are transforming research across disciplines. Whether you’re modeling text with large language models (LLMs), classifying biological samples, or predicting chemical properties, Research Computing is here to help.

  What We Support  

We provide hands-on support for:

•   LLMs and Generative AI: Support for ChatGPT, Claude, Llama, and other foundation models for summarization, translation, classification, and synthetic data generation
•   Supervised Learning: Including regression, classification, and ensemble models using scikit-learn, caret, or tidymodels
•   Unsupervised Learning: Techniques like clustering, dimensionality reduction (PCA/t-SNE), and topic modeling
•   Deep Learning: Using TensorFlow, PyTorch, or Keras for image, audio, or text-based research
•   Model Evaluation: Guidance on cross-validation, performance metrics, tuning, and reproducibility
•   R and Python Development: Best practices for data pipelines, reproducible workflows, and custom tools

  Who We Work With  

Researchers from a wide range of fields collaborate with us, including:

•   Biology: Image classification, gene expression modeling, pathway analysis
•   Chemistry: Structure–activity relationships, compound clustering, predictive modeling
•   Humanities: Natural language processing, generative authorship tools, topic modeling
•   Neuroscience: EEG classification, behavioral modeling, cognitive outcome prediction
•   Medicine & Public Health: Clinical text mining, diagnostic support, social determinants analytics
•   Environmental Sciences & Geography: Remote sensing, spatial modeling, risk classification

  Ready to Get Started?  

Whether you’re exploring machine learning for the first time or scaling a production model, our team can assist you from planning through publication.

Explore all our services to see how we can support your next research project.