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SpiNNcloud Systems GmbH
9h ago

PhD Candidate for Neuromorphic Approaches to Solving Combinatorial Optimization Problems Using Spiking Neural Networks on SpiNNaker2(m/w/x)

Dresden
Full-timeOn-site
AI/ML
Data Science

Description

In this research role, you will bridge the gap between neuromorphic computing and optimization by developing SNN-based solvers and deploying them on the advanced SpiNNaker2 system.

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Requirements

  • Willingness to travel for secondments
  • Participation in outreach and dissemination
  • Compliance with MSCA mobility rules
  • Two-year master’s degree or equivalent
  • Completed master's degree before start

Education

Master's degree
OR
Currently in higher education

Tasks

  • Derive mapping strategies for classical optimization algorithms to SNNs
  • Select appropriate neuron models and membrane parameters
  • Benchmark neuromorphic optimization implementations against classical solvers
  • Explore gradient-based and gradient-free SNNs for optimization
  • Apply research findings to real-world optimization problems at Neurobus

Tools & Technologies

YouTubeSocial media

Languages

EnglishBusiness Fluent

Benefits

Mentorship & Coaching

  • Interactions with doctoral network

Diverse Work

  • Interdisciplinary activities

Additional Allowances

  • PhD scholarship

Other Benefits

  • Rewarding and challenging position
  • Academic excellence
  • Academic freedom

Informal Culture

  • International team
  • Collegial respect
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