Research Fellow (Machine Learning & AI for Science)
Salary undisclosed
Checking job availability...
Original
Simplified
Accept ClosePress Tab to Move to Skip to Content LinkSearch JobsJob DescriptionJob Title: Research Fellow (Machine Learning & AI for Science)Posting Start Date: 19/03/2025Job Description:The Institute for Functional Intelligent Materials (I-FIM) is looking for postdoctoral research fellows to work on topics in machine learning and its scientific applications. The successful candidate will work with Principal Investigators in I-FIM on these topics. The main responsibilities of the position include conducting cutting-edge research in machine learning theory and algorithm research, with applications to materials and quantum sciences. Topics include (but are not limited to) the following:
- Theory and algorithm development for learning polymer dynamics and other complex systems
- Theory and algorithm development for learning and controlling deterministic and stochastic dynamics
- PhD in Applied Mathematics, Computer Science, Physics or related fields
- Strong knowledge in machine learning and deep learning
- Familiarity with basic theory of dynamical systems, ODEs, PDEs and stochastic processes
- Knowledge in computational physics and chemistry are desirable
- Ability to code in Python with at least one of the popular deep learning frameworks, e.g., Jax, PyTorch, etc
- Academic research experience with strong publication record. The candidate should have published in top field journals and conferences.
Accept ClosePress Tab to Move to Skip to Content LinkSearch JobsJob DescriptionJob Title: Research Fellow (Machine Learning & AI for Science)Posting Start Date: 19/03/2025Job Description:â €The Institute for Functional Intelligent Materials (I-FIM) is looking for postdoctoral research fellows to work on topics in machine learning and its scientific applications. The successful candidate will work with Principal Investigators in I-FIM on these topics. The main responsibilities of the position include conducting cutting-edge research in machine learning theory and algorithm research, with applications to materials and quantum sciences. Topics include (but are not limited to) the following:
- Theory and algorithm development for learning polymer dynamics and other complex systems
- Theory and algorithm development for learning and controlling deterministic and stochastic dynamics
- PhD in Applied Mathematics, Computer Science, Physics or related fields
- Strong knowledge in machine learning and deep learning
- Familiarity with basic theory of dynamical systems, ODEs, PDEs and stochastic processes
- Knowledge in computational physics and chemistry are desirable
- Ability to code in Python with at least one of the popular deep learning frameworks, e.g., Jax, PyTorch, etc
- Academic research experience with strong publication record. The candidate should have published in top field journals and conferences.