About this role
The intern will develop transformer-based foundation models for healthcare applications by processing longitudinal patient medical event sequences. Key tasks include data cleaning, model pre-training, fine-tuning, and evaluating performance across various prediction tasks.
Candidates should be Year 2 or 3 undergraduates in Computer Science, Data Science, or related fields with proficiency in Python and PyTorch. Familiarity with transformer architectures and version control tools like Git is required.
What they're looking for
PythonPyTorchTransformer ArchitecturesDeep LearningData PreprocessingData CleaningGitGitHub
Frequently asked questions
What does a Uni Internship Jan to July 2027 - Healthcare Foundation Model for Medical Event Sequences at Synapxe do?
The intern will develop transformer-based foundation models for healthcare applications by processing longitudinal patient medical event sequences. Key tasks include data cleaning, model pre-training, fine-tuning, and evaluating performance across various prediction tasks. Candidates should be Year …
What skills does this Uni Internship Jan to July 2027 - Healthcare Foundation Model for Medical Event Sequences role need?
Key skills for this role include Python, PyTorch, Transformer Architectures, Deep Learning, Data Preprocessing, Data Cleaning.
How much does a Uni Internship Jan to July 2027 - Healthcare Foundation Model for Medical Event Sequences at Synapxe pay?
The employer did not list a salary for this role. Most similar Singapore roles publish their band on the job page.
Is this Uni Internship Jan to July 2027 - Healthcare Foundation Model for Medical Event Sequences role remote, hybrid, or on-site?
This role is on-site, based in Singapore.
How do I apply for this Uni Internship Jan to July 2027 - Healthcare Foundation Model for Medical Event Sequences role?
You can apply directly on Synapxe's careers page. ApplyLah can tailor your résumé and cover letter to this exact role in seconds first.