Open Positions

Open Positions Related to Action's Activities

 

*Post-doc position on memristive neural networks*

Deadline: April 3, 2018
PostDoc (# positions: 1)

The energy efficiency of computation in the brain relies on its unique architecture with high parallelism and sparse memory/computing elements with no physical separation. This is enabled by resistive switching devices, such as the resistive switching memory (RRAM), the phase change memory (PCM), and the magnetoresistive memory (MRAM). These memristive devices can play the role of computing nano devices and plastic synapses in a neural network. Our group is currently developing spiking neural networks with memristive device, where the device physics enables learning and other computing primitive of the brain.

This open postdoc position aims at the study of brain-inspired devices and spiking neural networks. RRAM devices will be fabricated in the clean room Polifab, while the neural networks will be designed and developed on printed circuit board (PCB) with discrete elements. After the electrical characterization, various spiking neural networks will be developed with memristive devices connected to a microcontroller serving as input/output hub. The objective of the work is to demonstrate spiking neural networks for neuromorphic computing with synaptic time dependent plasticity. Results of the testing will serve as input for the development of integrated circuits for brain-inspired in-memory computing.

The gross salary will be 28,000 EUR/year. The position is for one year and renewable. For more information contact daniele.ielmini@polimi.it.

 

 

*Royal Society PhD Studentships in Reconfigurable Memristor Technologies and Circuits*

PhD Studentships (# positions 2)

Applications are invited for a prestigious Royal Society PhD Studentship to be filled as soon as possible. The scholarship will fund students for their tuition fees, a bursary to cover living expenses (£14,777 per year) and a Research Training Support Grant for research consumables and conference attendance. This role will be based at the Electronic Materials and Devices Research Group within the Zepler Institute and will use state-of-the-art facilities at the Southampton Nanofabrication Centre.

Please find further information in the attachments (PhD Reconfigurable Circuits, PhD Memory Technology)

For more information contact T.Prodromakis@soton.ac.uk 

 

 

*PhD scholarships at the Agrate Unit of CNR-IMM, Agrate Brianza (Milano area), Italy*

PhD Studentships (# positions 3)

The 3 scholarships are sponsored at the University of Milano Bicocca, for the 34th cycle (1 November 2018 - 30 October 2021) of the Phd Program in Materials Science and Nanotechnology. The call is currently open and will close on June 7th, 2018.

The 3 research projects available at the CNR- IMM and more information on the call are included in the following attached files. (PhD MaterialScience and Nanotechnology, Phd Scholarships CNR-IMM Italy)

For further information please contact the supervisor indicated for each project.

 

*PostDoctoral Fellowships & PhD Studentships, Electronic Materials & Devices Research Group, University of Southampton

PostDoctoral Fellowships (#5), PhD Scholarships (#2)

You can find more details about the positions here.

For more information contact T.Prodromakis@soton.ac.uk

 

*PhD scholarships at the University of Hull, UK*

Development of ultra-high sensitivity and selectivity nanogap electrode apta-sensors for mapping the prevalence of hormones in aquatic systems with Neil Kemp (nanogap electrode sensors) and Jeanette Rotchell (hormones in the environment). Pharmaceuticals and other anthropogenic compounds are found in the aquatic environment often at extremely low levels, yet are still capable of toxic impacts that require monitoring. A new advancement in nanoscale sensor technology at Hull, culminating in the development of a label-free, capacitive nanogap sensor with ultra-high sensitivity and selectivity, has the potential to bring a new dimension to environmental sensing. It avoids labour intensive collections and lab-based analytical assessment using large and expensive equipment. The PhD project will improve the fabrication methodology of the device and better understand the underlying physics of how the device functions. The ultimate aim will be to build a hand-held or remote prototype sensor that targets a number of EU Watch List chemicals, such as estrogens. The PhD student will develop advanced nanotechnology skills involving chip design, cleanroom fabrication methods, aptamer electrode functionalization methods and AC impedance spectroscopy measurement techniques. Working with our partners we will also aim to trial remotely stationed prototypes that are wirelessly linked to the cloud. The candidate should have a degree in Physical or Engineering Sciences or a related discipline.

 

https://www.findaphd.com/search/ProjectDetails.aspx?PJID=101702 

or

https://www.jobs.ac.uk/job/BNO935/phd-scholarships-sensing-and-safeguarding-the-water-environment-6-phd-scholarships 

 

The PhD position is part of cluster of 6 fully funded studentships (two of these are in Physics). The fully list of positions is below

(1) Mapping heavy metal pollution in river water with paper-based devices through citizen science

https://www.findaphd.com/search/ProjectDetails.aspx?PJID=101698

 

(2) Analysis-on-a-roll platforms for automated and high frequency remote sensing of natural geochemical fluxes

https://www.findaphd.com/search/ProjectDetails.aspx?PJID=101699

 

(3) Unravelling micro-plankton populations through lab-on-a-chip-based sorting and analysis platforms

https://www.findaphd.com/search/ProjectDetails.aspx?PJID=101700

 

(4) Cutting edge optical spectroscopy for sensing particulate pollutants in aquatic systems

https://www.findaphd.com/search/ProjectDetails.aspx?PJID=101701

 

(5) Development of ultra-high sensitivity and selectivity nanogap electrode apta-sensors for mapping the prevalence of hormones in aquatic systems

https://www.findaphd.com/search/ProjectDetails.aspx?PJID=101702

 

(6) Modelling Environmental Data Systems with Deep Learning

https://www.findaphd.com/search/ProjectDetails.aspx?PJID=101703