20 beste Stellen als applied ai, forward deployed machine learning engineer in münchen, by – aktuell auf Personalsuche

MASTERARBEIT – SPIKING NEURAL NETWORKS IN THE PHYSICAL LAYER OF WIRELESS COMMUNICATION SYSTEMS (M/F/D)
fortiss GmbH —München
- Doktorat
- Master
- Machine Learning
Director of AI & Biometrics
Tools for Humanity —München
- Vollzeit
- Forschungserfahrung
- Machine Learning
- Künstliche Intelligenz
External Lecturer on a fee basis Applied Data Engineering f/m/d
SRH University —München
- Doktorat
- Master
- SQL
NPI - Product Technical Expert (m/f/d) - for semiconductor industry
Applied Materials —Heimstetten
- 70.400 € – 96.800 € pro Jahr
- Vollzeit
- Master
- Bachelor
- Führungserfahrung
Data & AI Consultant (m/w/d)
The Nunatak Group GmbH —München
- Vollzeit
- Azure
- Management-Erfahrung
- Informatik
- Weiterbildungsprogramme
AI Deployment Strategist - Munich, Germany
Mistral AI —München
- Vollzeit
- Vertrieb
- JavaScript
- Künstliche Intelligenz
- Mitgliedschaft im Fitnessstudio
Manufacturing Quality Engineer (m/f/d) - for semiconductor industry
Applied Materials —Heimstetten
- Vollzeit
- Bachelor
- Produktion
Working Student (m/f/d) Data Science Computer Vision / IdentityCheck
CHECK24 —München
- Teilzeit
- Informatik
- Machine Learning
- Python
- Flexible Arbeitszeiten
- Kostenlose Verpflegung
Lecturer on a fee basis AI in Life Sciences and Bioinformatics f/m/d
SRH University —München
- Doktorat
- Master
- Machine Learning
AI & Innovation Senior Engineer
The Exploration Company —München
- Vollzeit
- Azure
- ERP-Systeme
- AWS
- Umzugskostenzuschuss
Project Manager AI & Engineering (m/f/d)
TWT Science & Innovation —München
- Vollzeit
- Hybrides Arbeiten
- Doktorat
- Informatik
- Unternehmensentwicklung
R&D Verification & Qualification Engineer (m/f/d) - Semiconductor Industry
Applied Materials —Heimstetten
- 70.400 € – 96.800 € pro Jahr
- Vollzeit
- Doktorat
- CAD
- Datenanalyse
Junior Material Planner (m/f/d) for semiconductor inspection systems/electron microscopy
Applied Materials —Heimstetten
- 70.400 € – 96.800 € pro Jahr
- Vollzeit
- Microsoft Excel
- Microsoft Office
- Mit Reiseanteil
Electrical Engineer (m/f/d) - for semiconductor industry
Applied Materials —Feldkirchen
- 70.400 € – 96.800 € pro Jahr
- Vollzeit
- Mit Reiseanteil
AI Agent Specialist (d/f/m)
Flexa —München
- 58.000 € – 70.000 € pro Jahr
- Vollzeit
- Master
- APIs
- Künstliche Intelligenz
Direkt bewerben
Space Situational Awareness Engineer
OKAPI:Orbits GmbH —München
- Vollzeit
- Wartung
- Java
- Master
- Flexible Arbeitszeiten
Direkt bewerben
6 Tage
Senior Solutions Architect, Generative and Physical AI - NVAITC
NVIDIA —München
- Vollzeit
- Doktorat
- Informatik
- Forschungserfahrung
4 Tage
Solution Architect, Computer Vision – Media and Entertainment
NVIDIA —München
- Vollzeit
- Doktorat
- Informatik
- Master
Supplier Quality Engineer (m/f/d) - semiconductor industry
Applied Materials —Heimstetten
- 70.400 € – 96.800 € pro Jahr
- Vollzeit
- Master
- Bachelor
- Mit Reiseanteil
Application Engineer (m/f/d) - semiconductor industry
Applied Materials —Feldkirchen
- 70.400 € – 96.800 € pro Jahr
- Vollzeit
- Mit Reiseanteil
- Produktion
- Elektrotechnik

Ich möchte aktuelle Job-E-Mails für Stellen als applied ai, forward deployed machine learning engineer in münchen, by erhalten

Wenn Sie sich bei Ihrem Konto anmelden, stimmen Sie den Nutzungsbedingungen, den Richtlinien zur Verwendung von Cookies sowie der Datenschutzerklärung von SimplyHired zu.

Weitere Job-Standorte erkunden

applied ai, forward deployed machine learning engineer jobs near münchen, by

MASTERARBEIT – SPIKING NEURAL NETWORKS IN THE PHYSICAL LAYER OF WIRELESS COMMUNICATION SYSTEMS (M/F/D)

fortiss GmbH -
München

Jetzt bewerben

Details zur Stelle

Qualifikationen

MATLAB
Doktorat
Master
Machine Learning
Python

Vollständige Stellenbeschreibung

fortiss GmbH Jobportal
Collage Thesis

Who are we?

fortiss is the research institute of the Free State of Bavaria for software-intensive systems and services with headquarters in Munich. The institute currently employs around 150 employees, who collaborate on research, development and transfer projects with universities and technology companies in Bavaria, Germany and Europe. Research is focused on state of the art methods, techniques and tools of software development, systems & service engineering and their application to reliable, secure cyber-physical systems, such as the Internet of Things (IoT). fortiss has the legal structure of a non-profit limited liability company (GmbH). Its shareholders are the Free State of Bavaria (as majority shareholder) and the Fraunhofer Society for the Promotion of Applied Research.

This master’s thesis will be jointly supervised by the Neuromorphic Computing team at fortiss and the ACES Lab at the Chair of Theoretical Information Technology.

In the design of wireless communication systems, models, such as channel models, have traditionally played a crucial role. However, these models always represent an idealized simplification and cannot fully capture all practical complexities. In contrast, data-driven approaches based on deep neural networks eliminate the need for explicit modeling and therefore have the potential to outperform classical designs. Current research explores deep learning techniques for tasks such as channel estimation, signal detection and modulation / demodulation, channel encoding and decoding, and physical-layer authentication.

Spiking neural networks (SNNs) are a novel type of neural network and differ fundamentally from conventional deep learning models by incorporating temporal dynamics and event-driven computation. SNNs operate using discrete spikes, similar to biological neurons, offering advantages in energy efficiency and temporal processing. Due to their event-driven, energy-efficient nature, SNNs are gaining attention in communications research.

This thesis focuses on designing and implementing SNNs to address selected physical-layer tasks, such as channel estimation. Initially, the performance of the implemented SNN will be evaluated through simulations of the SNN on GPUs. Subsequently, the network will be deployed on the best suitable specialized hardware platform (such as SpiNNaker2, Pulsar, Loihi 2, Akida 2) to assess real-time performance under practical constraints, including latency and energy consumption. Furthermore, data from USRP X410 software-defined radios (SDRs) will be utilized to study the performance on real-world data.

Your tasks:

Literature review and collegial choice of the most appropriate task (channel estimation, signal detection, channel encoding, interference management) for an SNN implementation. Considered will be the maturity of the state-of-the-art, hardware constraints, hardware capabilities, and implementation complexity
Design and implementation of an SNN (selecting a suitable neuron model, encoding scheme, and learning algorithm) for the selected task in software (CPU/GPU)
Port and deployment of the SNN on neuromorphic hardware
Performance evaluation (with synthetic and real-world data) and comparison to traditional approaches

Your profile:

Knowledge of wireless communication systems
Knowledge of neural networks and classical AI frameworks
Programming experience in MATLAB and Python
Experience with spiking neural networks (SNNs) and spiking frameworks is a plus

Did we catch your interest?

Please submit your application via this fortiss application form AND email it to Ullrich Mönich ([email protected]) with the subject line “Master’s thesis: Neuromorphic Comm”, including your CV and academic transcript.

Job-ID: NC-MA-01-2026
Contact: Dr. Axel von Arnim

Jetzt bewerben

Erweiterte Suche

applied ai, forward deployed machine learning engineer Jobs in münchen, by

MASTERARBEIT – SPIKING NEURAL NETWORKS IN THE PHYSICAL LAYER OF WIRELESS COMMUNICATION SYSTEMS (M/F/D)

Director of AI & Biometrics

External Lecturer on a fee basis Applied Data Engineering f/m/d

NPI - Product Technical Expert (m/f/d) - for semiconductor industry

Data & AI Consultant (m/w/d)

AI Deployment Strategist - Munich, Germany

Manufacturing Quality Engineer (m/f/d) - for semiconductor industry

Working Student (m/f/d) Data Science Computer Vision / IdentityCheck

Lecturer on a fee basis AI in Life Sciences and Bioinformatics f/m/d

AI & Innovation Senior Engineer

Project Manager AI & Engineering (m/f/d)

R&D Verification & Qualification Engineer (m/f/d) - Semiconductor Industry

Junior Material Planner (m/f/d) for semiconductor inspection systems/electron microscopy

Electrical Engineer (m/f/d) - for semiconductor industry

AI Agent Specialist (d/f/m)

Space Situational Awareness Engineer

Senior Solutions Architect, Generative and Physical AI - NVAITC

Solution Architect, Computer Vision – Media and Entertainment

Supplier Quality Engineer (m/f/d) - semiconductor industry

Application Engineer (m/f/d) - semiconductor industry

Ich möchte aktuelle Job-E-Mails für Stellen als applied ai, forward deployed machine learning engineer in münchen, by erhalten

Related Searches

Weitere Job-Standorte erkunden

Who are we?

Your tasks:

Your profile:

Did we catch your interest?

Tools für Jobsuchende

Arbeitgebertools

Durchsuchen

Bleiben Sie in Kontakt