Announcement:
Northwestern-Argonne Institute of Science and Engineering Undergraduate Summer Research Internships
at Argonne National Laboratory
Overview: The Northwestern-Argonne Institute of Science and Engineering (NAISE) seeks applicants for summer research internships at Argonne National Laboratory.
Objectives are for students to gain experience working at a national laboratory and for the university and the laboratory to build collaborations in research areas strategic
to both institutions.
Successful applicants will spend 10 weeks in the program over the summer quarter with one mentor from each institution. Students will conduct the majority of the work at Argonne, making use of the NAISE carpool vehicles to travel there. Concluding symposia with research presentations will be held at both Argonne and Northwestern.
To apply: Submit a 1-page cover letter expressing your choice of research area (see options 1-4 below), an explanation of this choice, a resume (1-2 pages),
and two letters of recommendation
by FEBRUARY 15, 2018
to naise_summer@northwestern.edu
Research Areas:
1. Synthetic Biology and Materials Science and Design
* Developing a framework to produce materials that arise from hierarchical assembly of monomeric building blocks (proteins, polymers, inorganic particles, magnetic particles, etc.)
* Harnessing materials science to provide insight into biological mechanisms
2. Machine Learning Applied to Materials Imaging
* Applying spatial tracking and automatic alignment to materials images and using machine learning to label images and acquire metadata.
* Using active learning to determine uncertainty levels in images and incorporate human input for regions
of high uncertainty.
3. Energy-Water Nexus
* Controlling biofilm formation through materials engineering
* Developing membrane pretreatment methods to cut scaling
4. Advanced Manufacturing
* Scalable synthesis of battery materials, catalysts, in-situ x-ray for additive manufacturing
* Multiscale tools for materials and process design
* Sustainable manufacturing
* Advanced coatings design
* Machine learning for manufacturing
* Integrated computational materials engineering (ICME)
* Process modeling |