Research Scientist

Responsibilities

• Design and implement novel machine learning models and methods for self-supervised learning, survival analysis, multi-modal learning, causal inference and interpretability.
• Translate machine learning and statistics papers into production-ready code.
• Build robust model evaluation frameworks and monitor model performance.
• Disseminate the results by co-authoring research papers and abstracts.
• Collaborate with a multidisciplinary team of engineers and scientists. Co-mentor our team of research engineers.

• PhD degree in machine learning or statistics.
• Passion for research, attention to detail and ability to drive tasks to completion. Strong preference will be given to candidates with papers in A
  * conferences (e.g. ICML, ICLR, NeurIPS).
• Excellent understanding of core machine learning concepts.
• Excellent knowledge of the foundations of statistics, linear algebra, probability and machine learning.
• Excellent skills in Python and PyTorch.
• Experience in deep learning and at least one of {self-supervised learning, survival analysis, multi-modal learning, domain adaptation, causal inference, model interpretability, computational pathology}.