NOVEL HARDWARE FOR MACHINE LEARNING - EXPERIMENTAL PHYSICIST OR FPGA ENGINEER

University of Naples Federico IINovel Hardware for Machine Learning - Experimental Physicist or FPGA EngineerInstitution DescriptionThe University of Naples “Federico II” is a public university in Naples, Italy.
Founded in , it is the oldest public non-sectarian university in the world, and is now organized into 26 departments.
he Department of Physics “E.
Pancini” has the largest academic staff among Physics Departments in Italy.
The broad research programs at the Department include, Astroparticle, Condensed Matter, Nuclear, Subnuclear and Theoretical Physics, Physics of the Universe, Applied Physics, Physics for Education and History of Physics.
Further details are available atwww.
isica.
nina.
t/en_GB/homeIntroductionAre you a Master or PhD graduate in Experimental Physics or Electronics Engineering? Are you experienced in the field of FPGA design and/or in-memory computing? Are you willing to spend 18 months as a fellow at the oldest public University of the world? We are seeking to expand our team developing novel reconfigurable processors based on FPGAs and emerging devices.
The aim is to implement efficient and fast machine learning algorithms for particle physics experiments.
This will involve R&D, characterization of novel devices, testing, integration and demonstration on prototypes, all contributing to future of physics.
Join us!FunctionsYou will join the team of the REconfigurable Electronics Laboratory (REEL) of the Department of Physics “E.
Pancini”, which performs R&D and electronics design for physics experiments world-wide, including experiments at CERN (Geneva, Switzerland) and KEK (Tsukuba, Japan).
The team is opening an exciting new opportunity for a young researcher.
s a member of the team you will.
esign and test firmware for state-of-art FPGAs implementing very-high-resolution time-to-digital converters and digital-to-time converters.
esign complex control software for advanced instrumentation for the characterization of memristive crossbars and other emerging hardware devices for neuromorphic computing.
articipate in conceptual studies for defining IO circuits for coupling FPGAs devices to neuromorphic computing devices.
mplement Machine Learning algorithms on FPGAs and hybrid systems including FPGAs coupled with neuromorphic computing devices.
articipate in group meetings, document firmware, software and test procedures, and present highlights of your work at international conferences.
mployment ConditionsContract type.
Post-doc fellowship (also non-PhD graduates can apply) for 14 months.
The net salary depends on taxes, however assuming no other incomes, it will be nearly EUR/month.
The appointment is expected to be as early as Apr.
.
ow to applyThe formal call is now open.
ttp://www.
nina.
t/documents///FIS_AR-42__bando.
dfPlease scroll the PDF down to page 9 for the English version.
pplications must reach us before Jan.
, by filling in the dedicated application forms and sending them to the specified address.
After the deadline, a link for a remote connection via MS Teams will be provided to applicants for an interview.
ontactsFor scientific questions about the role, please contactDr.
Raffaele Giordano – Associate Professoremail.
case of questions about the application process or administrative aspects of the fellowship please refer toDr.
Rocco Russoemail.