AI Research Scientist (Europe/UK - Remote)

Contribute to the entire development cycle of our cutting-edge large deep learning models;

Prepare datasets, design architectures, implement solutions, train and evaluate models to improve our products;

Collaborate across engineering and clinical teams to translate cutting-edge AI research into practical applications that have clinical implications;

Work towards long-term ambitious research goals based on developing novel solutions, while identifying immediate milestones;

Turning novel research ideas into working code;

Influence progress of relevant research communities by producing publications.

A PhD, or be currently enrolled in a PhD program and obtaining the degree prior to the start of employment, in Computer Science, Machine Learning, or a highly technical field;

A track record of research publications in peer-reviewed academic conferences or journals;

Proficiency in Python and experience with common machine learning frameworks (e.g., PyTorch, JAX, TensorFlow);

Demonstrated ability to design experiments, and analyze and interpret their results;

Must have or be able to obtain work authorization in Portugal.

A strong research background and first-author publications in top-tier AI conferences (e.g., NeurIPS, ICML, ICLR, CVPR, COLM, ACL, EMNLP);

Deep expertise in one or more of the following areas: Large Language Models (LLMs), multimodal learning (vision, speech), deep learning, or reinforcement learning (RL);

Alternatively, a proven track record of exceptional research contributions in another highly quantitative field (e.g., Physics, Applied Mathematics, Computational Statistics), coupled with a strong passion to apply your skills to AI for healthcare;

Industry experience taken during or after the PhD. e.g., Research Internships;

Experience taking research ideas from conception to implementation, including developing and debugging complex systems;

Strong communication skills and a history of effective collaboration on research projects;

A broader record of research excellence, demonstrated through grants, fellowships, patents, impactful open-source contributions, or relevant internships.