Postdoctoral researcher
We are seeking a PREP post-doctoral candidate to fill an associate position within the Materials Measurement Science Division. This postdoc will be a key member of a new project to develop an autonomous platform for growing and testing novel metal organic framework (MOF) materials for applications in carbon capture (https://doi.org/10.1016/j.xcrp.2022.101063). Specifically, the position will involve commissioning and operating a robotic platform for the synthesis of MOF materials along with carrying out high-throughput characterization assays and providing chemical insight into the design of an autonomous workflow. Successful candidates must have a background in MOF (or other similar chemical frameworks) synthesis and characterization.
The postdoc will join a group which is focused on pioneering applications of modern machine learning methods, FAIR data infrastructure, and experimental automation to materials characterization (metrology) methods across all portions of the structure-processing-properties-performance relationship. Specific group research focus areas include the development of interpretable and trustworthy algorithms for Scientific Artificial Intelligence and active learning, integrating FAIR data management practices throughout the research lifecycle, and developing innovative on-demand material synthesis and characterization platforms for closed-loop materials development.
Development of an autonomous platform for growing and testing novel metal organic framework (MOF) materials for applications in carbon capture
- A Master’s degree in Computer Science, Engineering, Manufacturing, or a related field.
- 2 years of relevant experience.
- Familiarity with MOFs synthesis.
- Ability to work with real-time event data at scale.
- Familiarity with scripting languages/coding.
- providing chemical insight into MOFs synthesis procedures and the design of an autonomous workflow
- commissioning and operating a robotic platform for the synthesis of MOF materials
- carrying out high-throughput characterization assays
- recording procedures, metadata, and outcome for all synthesized MOFs in both successful and unsuccessful case
- contributing to database creation and maintenance for synthesis data
- Presenting results at internal meetings, and occasional meetings with external stakeholders.
- Publishing results on peer-reviewed journals