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Machine Learning Researcher

2 months ago

Cambridge, Massachusetts, United States DeepRec Full time

Job Title: Machine Learning Scientist

Company: DeepRec


We are seeking a highly skilled Machine Learning Scientist to join our innovative team at DeepRec. As a key member of our team, you will be responsible for designing, building, and scaling supervised machine learning models for active learning and Bayesian optimization in materials synthesis and performance.


Key Responsibilities:


  • Develop and implement advanced machine learning algorithms for uncertainty quantification and active learning in materials discovery.
  • Collaborate with our computational team to identify materials design pathways and their synthesis.
  • Work with our infrastructure and automation teams to integrate datasets of multiple fidelities and sources for data-driven materials discovery.
  • Drive material discovery and development with our experimental team, building domain-specific acquisition functions.
  • Stay up-to-date with the latest machine learning research through literature reviews, conferences, and networking.
  • Report findings to stakeholders and leadership through written reports and presentations.


Qualifications:



  • Experience with uncertainty quantification, active learning, and Bayesian optimization.
  • Skilled in implementing, evaluating, and tuning supervised models in a Bayesian optimization context.
  • Proficiency in machine learning frameworks (PyTorch/TensorFlow/Jax) and the Python data science ecosystem (Numpy, SciPy, Pandas, etc.).
  • Experience with cloud computing services for training and evaluating models.
  • PhD in Computer Science, Applied Mathematics, or a related field with a focus on machine learning.
  • Independent thinker with strong attention to detail.
  • Demonstrated industry experience or notable academic achievement.
  • Excellent communication and presentation skills.
  • Enthusiastic about working in a fast-paced, entrepreneurial, and technical setting.


Preferred Qualifications:


  • Experience using AWS services.
  • Experience with integrating machine learning in experimental workflows.


We look forward to hearing from you.