PhD student Organic Neuromorphic Arrays for Smart Biosensors
PhD student Organic Neuromorphic Arrays for Smart Biosensors
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Functieomschrijving
Project
Brain-inspired (neuromorphic) computing has recently demonstrated major advancements in pattern and image recognition as well as classification of unstructured (big) data. Today software systems known as neural networks can not only translate languages and classify images but are also successfully implemented in recognizing diseases, predict optimised routes and can unlock your phone. In an attempt to mimic biological synapses to approach the energy efficiency of the brain, resistance switching (memristor) devices have been developed but these suffer from high switching energies and lack sufficient programming range. This project will be based on a remarkably tunable organic memristive device (van de Burgt, Nature Materials, 2017) with a fundamentally different working mechanism, based on the controlled ion injection into the bulk of the conductive polymer. The conductance (or synaptic weight) of this artificial synapse can thus be accurately tuned, crucial for low-energy analogue computing. In this project, we will tackle the next major challenge:
To create an interconnected network of artificial synapses to obtain a true neuromorphic array capable of learning and classification applied in a smart biosensor.
The fabrication of crossbar arrays will be investigated that will lead to the development of a smart biosensor that can be 'trained' using a linear combination of ionic sensor inputs and which will serve as a starting point for future lab-on-a-chip cell classification applications.
Brain-inspired (neuromorphic) computing has recently demonstrated major advancements in pattern and image recognition as well as classification of unstructured (big) data. Today software systems known as neural networks can not only translate languages and classify images but are also successfully implemented in recognizing diseases, predict optimised routes and can unlock your phone. In an attempt to mimic biological synapses to approach the energy efficiency of the brain, resistance switching (memristor) devices have been developed but these suffer from high switching energies and lack sufficient programming range. This project will be based on a remarkably tunable organic memristive device (van de Burgt, Nature Materials, 2017) with a fundamentally different working mechanism, based on the controlled ion injection into the bulk of the conductive polymer. The conductance (or synaptic weight) of this artificial synapse can thus be accurately tuned, crucial for low-energy analogue computing. In this project, we will tackle the next major challenge:
To create an interconnected network of artificial synapses to obtain a true neuromorphic array capable of learning and classification applied in a smart biosensor.
The fabrication of crossbar arrays will be investigated that will lead to the development of a smart biosensor that can be 'trained' using a linear combination of ionic sensor inputs and which will serve as a starting point for future lab-on-a-chip cell classification applications.
Specificaties
- max. 38 uur per week
- Eindhoven Bekijk op Google Maps
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Technische Universiteit Eindhoven (TU/e)
Functie-eisen
Requirements
We are looking for a candidate with a background in materials science, (microsystems) engineering, electrical engineering or applied physics or relevant discipline. Given the multidisciplinary character of the proposed research the ideal candidate has experience in organic materials science, device physics and circuit engineering. Furthermore, the candidate has a hands-on attitude, experimental experience and can work independently as well as collaborate with others.
Embedding
The PhD student will be directly supervised by prof. Yoeri van de Burgt assistant professor in the microsystems group headed by prof. Jaap den Toonder. The microsystems group is part of the Institute of Complex Molecular Systems (ICMS). The microsystems group manages the Microfab lab, a state-of-the-art micro fabrication facility that houses a range of micro-manufacturing technologies. The project will be done in close collaboration with prof. Rene Janssen (Chemistry, TUE) as well as collaborations with prof. Salleo at Stanford University (US) and prof. Malliaras at University of Cambridge (UK).
We are looking for a candidate with a background in materials science, (microsystems) engineering, electrical engineering or applied physics or relevant discipline. Given the multidisciplinary character of the proposed research the ideal candidate has experience in organic materials science, device physics and circuit engineering. Furthermore, the candidate has a hands-on attitude, experimental experience and can work independently as well as collaborate with others.
Embedding
The PhD student will be directly supervised by prof. Yoeri van de Burgt assistant professor in the microsystems group headed by prof. Jaap den Toonder. The microsystems group is part of the Institute of Complex Molecular Systems (ICMS). The microsystems group manages the Microfab lab, a state-of-the-art micro fabrication facility that houses a range of micro-manufacturing technologies. The project will be done in close collaboration with prof. Rene Janssen (Chemistry, TUE) as well as collaborations with prof. Salleo at Stanford University (US) and prof. Malliaras at University of Cambridge (UK).
Arbeidsvoorwaarden
We offer you:An exciting job in a dynamic work environment The possibility to present your work at international conferences. A full time appointment for four years at Eindhoven University of Technology (www.tue.nl/en) The salary is in accordance with the Collective Labour Agreement of the Dutch Universities, increasing from € 2,222 per month initially, to € 2,840 in the fourth year. An attractive package of fringe benefits, including end-of-year bonus (8,3% in December), an extra holiday allowance (8% in May), moving expenses and excellent sports facilities.
