Match based on: climate, sustainability, NEC registered organization
PhD candidate developing system-theoretic frameworks and energy-based learning algorithms for analog circuits. Requires a Master's in a related field and a strong mathematical background. Project embedded in the ERC E-BLOCS at the University of Groningen.
University of Groningen
Groningen
Fulltime
Part-time

Description

PhD position in systems and control theory for energy-based learning, focused on developing new mathematical foundations for energy-efficient computing. The project sits at the intersection of systems and control theory, optimization, circuit theory, and neuromorphic computing, aiming to advance theory for learning in analog circuits and dissipative networks. Learning is viewed as a feedback interconnection between continuous-time circuit dynamics and optimization algorithms, with the goal of deriving energy-inspired, local learning rules.

Job requirements

  • Master's degree in Systems and Control, (Applied) Mathematics, Electrical Engineering, or a closely related field.
  • Strong mathematical background and an interest in conducting theoretical research.
  • Excellent English communication skills, both written and spoken.
  • Strong analytical abilities, creativity, persistence, and the ability to collaborate effectively.
  • Familiarity with circuit theory, networked systems, machine learning, or neuromorphic computing is an advantage but not required.

Tasks

  • Develop a system-theoretic framework that models learning as the feedback interconnection between continuous-time circuit dynamics and optimization algorithms.
  • Design novel energy-based learning algorithms for training analog circuits directly from input-output data.
  • Develop fully decentralized learning rules that rely on local circuit information and suit large-scale systems.
  • Establish rigorous theoretical guarantees for convergence and scalability of the proposed learning algorithms.
  • Extend the theory from analog circuits to more general dissipative networks.
  • Test and validate the developed methods.
  • Publish research findings in leading international journals and conferences and present at scientific meetings.
  • Contribute to teaching activities and supervise Bachelor's and Master's students where appropriate.

Working conditions

  • Salary in accordance with the collective labor agreement for Dutch universities: €3,204 gross per month in the first year up to €4,051 gross per month in the fourth year for a full-time position.
  • 232 vacation hours per year based on a 38-hour workweek; options to work more or fewer hours in exchange for more or fewer free hours.
  • End-of-year bonus of 8.3% and a holiday allowance of 8%.
  • Extensive opportunities for personal and professional development and a PhD training program; enrollment in the Graduate School of Science and Engineering.
  • Teaching expectation: employed PhD candidates are expected to spend 10% of their working hours on teaching for a full-time position.
  • Initial temporary position of one year with the option to renew for another three years; prolongation depends on sufficient progress indicating likely completion of the PhD within the remaining three years.

Description of the organization

The PhD position is at the University of Groningen within the Faculty of Science and Engineering, which covers disciplines from physics and biology to artificial intelligence and engineering. The successful candidate will join the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence and the Systems, Control and Optimization Group, which is part of the Jan C. Willems Center for Systems and Control.

The project is embedded within the ERC Starting Grant project "Energy-based learning of complex dynamical systems" (E-BLOCS) and offers collaboration within a lively research community, regular seminars, group meetings, and opportunities for international research visits and interdisciplinary training.

Skills suitable for this job type

personal skills and development
general programmes and qualifications not elsewhere classified
educational science
economy
Law
biology
earth sciences
physics
math
statistics
interdisciplinary programs and qualifications covering natural sciences, mathematics and statistics
computer use
development and analysis of software and applications
chemical technology and processes
mechanics and metal
motor vehicles, ships and aircraft
construction and road and hydraulic engineering
medicine
medical diagnosis and treatment technology
pharmacies
using foreign languages
negotiating and managing contracts and agreements
supervise, direct and coordinate projects
preparing documentation for contracts, applications and permits
analyzing and evaluating information and data
give feedback
collecting information from physical and electronic sources
managing information
teaching academic subjects or vocational training
assessing land and real estate
technical or academic writing
operating scientific equipment and laboratory equipment
developing educational programs
conduct scientific or market research
developing professional relationships and networks
presenting research and technical information
conducting studies and research
collaborate with others
using digital tools for collaboration and productivity
communicating with colleagues and customers
programming computer systems
communication, collaboration and creativity
analyzing scientific and medical data
design of industrial materials, systems and products
use precision measuring instruments
teaching and training
presenting general information
coaching and guidance
advise on legal matters, legislation and regulations and procedural matters
collecting and preparing samples and materials for testing
performing calculations
Transmission Control Protocol/Internet Protocol (TCP/IP)
Scalability
Modeling techniques
Date
Machine Learning (ML)
Internal policy
Framework (set of software components)
Write texts
Modeling work
nonlinear
Development
Presentations
Network
Analyze
Conferences
Math
Testing activities
Bicycle paths
Algorithms

Disclaimer

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