471 geprüfte KI-Jobs

Anforderungen

Depending on the specific projects above you seek to join, your profile should cover some of the skills listed below. Masters degree in electrical/electronic engineering, computer science, computer engineering, physics, or related field Good understanding of computer architecture and hardware accelerator design is beneficial For circuit implementations, strong electronics background with experience in design and simulation of analog, digital, or mixed-signal circuits, including SPICE and related tools is strongly desired For algorithms projects, a strong background in coding and advanced mathematics is strongly desired Programming experience in Python and familiarity with machine learning frameworks Knowledge of emerging memory devices and computing technologies is beneficial Excellent communication skills and the ability to work in a team are essential Very good command of written and spoken English with extensive vocabulary is required for the international working environment (at least B2 level according to the CEFR), ideally supported by a certificate confirming the language level. Our Benefits for You Research & Infrastructure: You will participate in a world-leading international research environment with state-of-the-art equipment Team & Environment: You will have the opportunity to work in the highly interdisciplinary and exciting field of neuromorphic and brain-inspired computing, collaborating with physicists, neuroscientists, materials scientists, and engineers Networking & Exchange: You will participate in (international) conferences and project meetings and actively build your scientific network Supervision & Support: We will accompany your doctoral studies with continuous, expert guidance from your academic supervisor Work-life balance: We offer flexible working hours to help you balance your professional and personal life.

You also have the option of flexible working (in terms of location), which is generally possible after consultation and in line with upcoming tasks and (on-site) appointments Annual Leave: You get 30 days of annual leave Knowledge & Development: Your professional development is important to us – we support you specifically and individually e.g., through training and networking opportunities specifically for doctoral candidates (JuDocS) Fair remuneration: Depending on your qualifications and assigned responsibilities, you will be classified according to pay group 13 (75%) of the TVöD-Bund. In addition to the basic salary, there is an additional year-end bonus under the collective pay agreement amounting to 75% of a monthly salary, as well as capital-forming benefits. All information about the TVöD-Bund collective agreement can be found on the BMI website (pay scale table on page 74 of the PDF download) Perspective: The position is initially for a fixed term of 3 years but with the prospect of longer-term employment Support for international employees: Our International Advisory Service makes it easier for international employees to get started In addition to exciting tasks and a collegial working environment, we offer you much more: https:/go.fzj.de/

Das wird geboten

We welcome applications from people with diverse backgrounds, e.g. in terms of age, gender, disability, sexual orientation / identity, and social, ethnic and religious origin. A diverse and inclusive working environment with equal opportunities in which everyone can realize their potential is important to us. The following links provide further information on diversity and equal opportunities: https:/go.fzj.de/equality and on specific support options for women: https:/go.fzj.de/womens-job-journey.

International applicants can find more information here: https:/go.fzj.de/job-journey-internationals

Zur Position

Place of Employment: Aachen Start Date: To the next possible date Salary: Pay Group 13 (75%) TVöD-Bund Application Deadline: The position will be published until it is successfully filled Index number: 2026D-0800 Your Job Several positions are available in distinct project areas: 1) Associative memory based computing: This project will utilize concepts including Dense Associative Memories and Modern Hopfield Networks to both a) physically realize such systems in electronics, particularly using novel content-addressable memory (CAM) designs, including tape-out opportunities, and b) exploring computing applications and algorithms that can leverage associative memories, including machine learning and LLMs, genomics, and classical data science methods (tree models, decision trees, finite automata). We will test these applications experimentally in taped-out IC chips. 2) Kolmogorov-Arnold Networks (KAN) as a promising complement to conventional neural networks. KANs offer efficient representations for complex nonlinear models, with unique research opportunities in algorithm and hardware co-design, particularly for resource-constrained environments.

Applications focus on edge intelligence, scientific computing, and emerging AI. The project tasks will include resource-aware training methods and hardware implementation, including the design, implementation, and verification of KAN accelerator architectures, as well as participation in tape-outs for custom integrated circuits. 3) In-hardware learning: More broadly than the above topics, our team seeks to build electronic hardware to support and implement local learning rules suitable for recurrent, nonlinear networks with internal state variables. The above projects provide suitable constrained architectures for this study, but the opportunity exists for more flexible explorations in both learning rule types and the physical realization.

This project will involve algorithm-hardware co-design ultimately targeting physical implemetations in integrated circuits composed of both CMOS and emerging memory technologies. An overarching theme of the projects is hardware-software co-design, where both circuits/ architecture and algorithms/applications are developed jointly in a team environment and with expert collaborators. Please specify in the application which project area you are specifically interested in.