IMT 33-2023 Master Thesis: Artificial Intelligence based sub-micron precision trapping on a dielectrophoresis platform
- Institute of Microstructure Technology (IMT)
- full time
ADEPT is a portable dielectrophoresis based manipulation platform, for the positioning and immobilization of micro meter sized dielectric objects, such as bacteria or micro beads. The system controls the amplitude, phase and frequency of the voltage signal applied to a circular array of up to six symmetrically arranged and independently controllable micro-electrodes (in a microfluidic chip). Using the forces generated by electric fields applied to the electrodes the particles are trapped with the microfluidic chip. More details on the system can be found in our publication (https://doi.org/10.1016/j.biosx.2023.100333). The trapping precision is currently around two micron and though this project we would like to use Artificial Intelligence (AI) to enhance the trapping performance.
The specific tasks within the project will be: (i) Integrate the camera into the already existing front end code; (ii) perform real time image segmentation (e.g. with existing deep learning-based cell segmentation) and generate desired control signals to accomplish high precision trapping by a smart algorithm of your choice; (iii) generation of an AI trap map using a random signal generator; (iv) design and fabrication of optoelectronics circuit boards.
You will be integrated in a larger team within the SPA-Lab. Within this project, you will use the infrastructure existent at the Institute of Microstructure Technology (IMT). This is a complete project, offering the possibility to work in an interdisciplinary project, giving you the opportunity to co-author conference and/or journal publications.
Field of Study: Electrical / Computer engineering
- good academic record (marks); curious about various aspects of science
- enthusiastic to work in a multidisciplinary environment
- independent thinker and team player
- in particular: strong interest in Artificial Intelligence, automation, firmware programming
- knowledge in microsystems/microfabrication/microfluidics is desirable
Carrasco Sanchez, Raquel
Tel: +49 721 608-42016