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AI4Science
微软研究院科学智能中心
万事俱备 “职”等你来
科学发展，人才为先
加入AI4Science，让我们一起改变世界！
BU introduction
部门介绍
微软研究院科学智能中心（AI4Science）是微软研究院（Microsoft Research）于2022年7月成立的全新团队，致力于通过在机器学习和自然科学交叉领域取得新的基础性研究进展，彻底改变人类理解自然世界以及与自然世界互动的方式，展现机器学习与自然科学交叉融合的诱人新能力。微软研究院科学智能中心是一个全球团队，科学智能中心的成员来自英国、中国、荷兰、德国和美国等多个国家，集结了机器学习、计算物理、计算化学、分子生物学、计算材料科学、软件开发和其他学科领域的世界级专家，共同致力于解决科学领域中最紧迫的挑战。
我们诚挚的向更多的自然科学家、AI 科学家、算法和系统工程师发出邀请，欢迎加入我们，一起用深度学习给自然科学带来变革性的影响。
热招岗位
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岗位名称
Senior Research SDE-多名
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岗位地点
北京、上海
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岗位职责
作为资深的 Research SDE，您的工作职责将涉及：
✦Architect, design, and implement scalable and robust solutions for machine learning and scientific research involving large volumes of heterogeneous data.
✦ Build and optimize distributed data processing and model building pipelines.
✦ Develop and maintain tools and technologies for building, training, optimizing, scaling machine learning solutions.
✦ Collaborate with cross-functional teams, including scientists, researchers, and software engineers.
✦ Document and share best practices across the organization.
✦ Maintain the highest standards in code quality and software design.
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任职要求
✦Master's degree or equivalent work experience in Computer Science, Physics, Engineering, Chemistry, Mathematics or a related field.
✦ Strong familiarity with Linux and the open-source ecosystem.
✦ 4+ years of experience working with machine learning and large datasets.
✦ In-depth understanding of machine learning frameworks (e.g., TensorFlow, PyTorch).
✦ 4+ years of experience building and optimizing distributed systems and large-data applications, including those using tensor accelerators or GPUs.
✦ Strong analytical, problem-solving, and communication skills.
✦ Passionate about pushing the boundaries of science.
✦ Prior experience developing high-performance scientific software is not required, but preferred.
扫码一键投递
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岗位名称
Researcher (All level) -多名
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岗位地点
北京、上海
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岗位职责
作为 AI4Science 的成员，我们希望你对机器学习保有高度的热情，和我们一起致力于世界级的科学研究。
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任职要求
✦ Master's degree or equivalent work experience in deep learning and reinforce learning, with publications in top ML conferences, e.g., NeurIPS, ICLR, ICML.
✦ Passion in science related problems, including but not limited to, materials science, chemistry, physics, and biology.
✦ Proficiency in Python and relevant ML libraries (e.g., PyTorch).
✦ Experience with transformer-based models (e.g., GPT, Llama).
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