AI/ML - Machine Learning Internship, Health AI
Apple Inc
Zurich, Switzerland
Job posting number: #7286284 (Ref:apl-200572834)
Posted: October 10, 2024
Job Description
Summary
We are looking for a machine learning research intern with a passion for applying machine learning research to challenging problems inspired by the health domain. You will join a close-knit team of highly accomplished and deeply technical research scientists and engineers passionate about delivering groundbreaking machine learning technologies to the health space. You will perform research by defining, crafting, implementing, and evaluating new machine learning models and algorithms to solve complicated problems involving unique data and objectives. We are seeking candidates with proven interest and experience — via publications — in developing and innovating machine learning methods.
The experience must reflect at least one of these areas:
- Causality and causal representation learning
- Combining scientific models with machine learning
- Physics-informed machine learning
- (Structured/unstructured) deep generative modelling
- Fair and robust machine learning
The experience must reflect at least one of these areas:
- Causality and causal representation learning
- Combining scientific models with machine learning
- Physics-informed machine learning
- (Structured/unstructured) deep generative modelling
- Fair and robust machine learning
Description
Your responsibilities include: Researching and implementing novel machine learning techniques (see Key Qualifications) for unique health data and problems. Length of the internship is flexible and can be up to multiple months.
Minimum Qualifications
- Ability to drive ambitious research independently.
- Skilled in explaining and communicating analyses and machine learning concepts to a broad technical audience.
- Proficiency developing machine learning solutions using Python and its associated ecosystem — numpy, pandas, Jax, PyTorch, etc.
Preferred Qualifications
- PhD student in machine learning/data sciences (CS, ECE, Statistics, Math, natural sciences, or other related fields).
