Details about Self-Driving Laboratories for Advanced Sustainable Materials Synthesis at University of Sheffield 2025
Self-Driving Laboratories for Advanced Sustainable Materials Synthesis at University of Sheffield 2025 is offered for PhD degree in the field of Chemical Engineering, Materials Science. You can apply to this scholarship here. The deadline for the sending your application is 10 Apr, 2025. This scholarship is provided by University of Sheffield and the value of this scholarship is Partial Funding, varies . This scholarship is open for: Open to citizens of UK.
- Degree: PhD
- Provided by: University of Sheffield
- Deadline: 10 Apr, 2025
- Scholarship value: Partial Funding, varies
Self-Driving Laboratories for Advanced Sustainable Materials Synthesis
- The Self-Driving Laboratories for Advanced Sustainable Materials Synthesis PhD project at the School of Chemical, Materials and Biological Engineering combines the power of artificial intelligence (AI), machine learning (ML), robotics, and automation to revolutionize the discovery and synthesis of advanced sustainable materials.
- This project aims to accelerate material development through automated, consistent, and reproducible experimental setups, helping to reduce raw material use and waste generation.
Eligibility
- This project is directly funded and is open to UK students who hold an upper second-class degree in Chemical Engineering, Materials Science and Engineering, or Chemistry.
- Applicants should be enthusiastic about chemical engineering, material synthesis, and multidisciplinary research, with a keen interest in AI-driven experiments.
Application Process
- Applications for this PhD program are accepted year-round.
- Interested candidates should contact the Department of Chemical, Materials and Biological Engineering directly to inquire about the application process and specific details regarding funding contributions, including fee waivers and potential bursaries.
Benefits/Value
- This PhD opportunity provides a chance to work with cutting-edge self-driving laboratory (SDL) technologies, gaining valuable experience in materials synthesis, reactor design, online monitoring, and machine-learning-directed experiments.
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