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Research Scientist, Machine Learning (PhD)

ataraxis.ai
Full-time
On-site
New York, New York, United States

About Ataraxis AI

Ataraxis AI is a VC-backed start-up working at the intersection of multi-modal AI, oncology, and precision medicine. We are building cutting-edge diagnostic tools to assist physicians in selecting the most optimal treatments for their patients.

We are a team of AI researchers, medical doctors and operators advised by a team of advisors who are pioneers in their respective fields, including the AI godfather, Yann LeCun, and oncologists at top cancer research institutes.

At Ataraxis, you will have a unique opportunity to shape not just the future of our company, but the future of healthcare. We are looking to bring on highly motivated candidates to fulfill this mission.

We operate with a flat organizational structure where every team member is expected to actively contribute. Leadership roles are earned by those who demonstrate initiative and deliver consistently high performance. Strong work ethic and the ability to prioritize effectively are essential. All candidates must communicate clearly, sharing insights accurately and concisely with teammates. We don’t use recruiters β€” each application is reviewed personally by a relevant team member and/or founders.

Responsibilities

  • Design and implement sophisticated machine learning models for feature engineering and selection, survival analysis, multi-modal learning, and model interpretation.

  • Convert research papers and statistical theory into production-ready systems.

  • Build robust and novel validation and optimization frameworks, monitoring model accuracy and optimizing it focused on clinically relevant metrics.

  • Writing research papers.

  • Co-mentoring our team of data scientists and research engineers.

Qualifications

  • PhD degree in machine learning or statistics.

  • Passion for research. Strong preference will be given to candidates with published papers in A* conferences (ICML, ICLR, NeurIPS).

  • Deep theoretical understanding of core machine learning concepts and mastery of foundational ML algorithms. Strong preference will be given to candidates with deep theoretical understanding of survival analysis and/or causal inference.

  • Excellent skills in Python and PyTorch.