обновлено 9 часов назад
Machine Learning Scientist/Senior Machine Learning Scientist (AI for Drug Discovery)
147 600 - 274 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Machine Learning Scientist/Senior Machine Learning Scientist (AI for Drug Discovery): Developing synthesis-aware machine learning methods, molecular design models, and active-learning pipelines for drug discovery with an accent on retrosynthesis, synthesis planning, molecular generation, and automated synthesis. Focus on designing batch synthesis-planning algorithms, integrating reaction and biochemical data, and optimizing experimental efficiency across synthesizable chemical spaces.
Location: South San Francisco, California, United States of America; also available in New York City.
Salary: $147,600–$274,000 for the ML Scientist level and $167,400–$310,800 for the Senior ML Scientist level in San Francisco. New York City ranges are $141,100–$262,100 and $160,100–$297,300, respectively.
Company
and Roche's Computational Sciences Center of Excellence applies artificial intelligence, data, and computational science to drug discovery and development.
What you will do
- Develop machine learning methods for synthesis-aware molecular design.
- Build models and workflows for retrosynthesis, synthesis planning, molecular generation, and search in synthesizable chemical spaces.
- Integrate proprietary reaction and biochemical data.
- Build robust, scalable pipelines for active-learning loops and automated or high-throughput synthesis.
- Design batch synthesis-planning algorithms and optimize chemical-space coverage, information gain, and experimental efficiency.
- Collaborate with computational and experimental researchers and academic partners, communicating results through publications, open-source releases, and conference talks.
Requirements
- Deep machine learning expertise and hands-on experience with modern approaches such as graph neural networks, sequence or language models, and reinforcement learning.
- Fluency in Python and experience with machine learning frameworks such as PyTorch or JAX.
- Strong foundations in linear algebra, probability, and optimization.
- Familiarity with chemistry, small-molecule data, cheminformatics toolkits such as RDKit or OpenEye, and synthesis-planning models.
- Experience with automated or high-throughput synthesis.
- PhD or equivalent research depth in machine learning, computational chemistry, chemical engineering, physics, statistics, or a related quantitative field, with evidence of scientific excellence.
Culture & Benefits
- Work alongside computational and experimental researchers across Roche and .
- Opportunity to contribute to self-driving drug discovery and medicines development.
- Benefits are available for the position.
- Relocation benefits are not available for this opportunity.
- A discretionary annual bonus may be available based on individual and company performance.
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