Master Thesis / Intern (all genders) â Quantization- and Fault-Aware Training and Development for Neuromorphic Computing
Master Thesis / Intern (all genders) â Quantization- and Fault-Aware Training and Development for Neuromorphic Computing
Employer Active
Job Alert
You will be updated with latest job alerts via email
Share
Job Alert
You will be updated with latest job alerts via email
Job Description
Fraunhofer IIS is very active in the fields of Embedded AI and Neuromorphic Computing. The Embedded AI group focuses on the development of concepts for analog and digital hardware architectures as well as the software frameworks required for the accelerated and energyefficient computation of neural networks (DNNs and SNNs). In addition the team creates and uses AI algorithms that run on resourcelimited embedded processors.
The Neuromorphic DNN hardware accelerators developed at Fraunhofer IIS use analog compute cores for ultralow energy consumption. However weights and activations need to be severely quantized (down to signed 3bit fixedpoint) and as for all analog hardware the compute cores exhibit effects like deviation of components from their nominal values and noise. For these reasons we have developed our own PyTorchbased library which extends Brevitas to tackle these effects already during the DNN training.
This work is focused on this internal Quantization and FaultAware Training and Inference tool. The tasks involve developing our tool further to support new features like new NN models and layer types e.g. LSTMs. Additionally this work includes implementing and testing new methods to keep up with the stateoftheart and expand on it in areas of training neural architecture search and edge AI.
Are you interested in researching and developing the latest methods of Quantization and FaultAware Training techniques in the exciting field of Neuromorphic Computing
Then have a look at our offer!
- You extend the Fraunhofer training tool for new NN models and layer types.
- You train quantized yet robust NN models e.g. for audio use cases using the forementioned tool.
- Optional: You research new and novel methods to enhance the training and resulting models.
- You are currently studying electrical or computer engineering or a related field.
- You are experienced in Python programming.
- You have a solid background in Machine Learning and Neural Networks.
- You have a good understanding of Edge AI/TinyML (e.g. quantization HW deployment).
- Flexible working hours
- Open and friendly team work
- Varied tasks with room for creativity
- Exciting seminars and events
- Networking with scientists
- Active contribution in applied research
- Interesting an innovative projects
You can start from now on. Your fulltime internship will last at least 3 months.
We would be happy to offer you the opportunity to write a bachelors or masters thesis in cooperation with us in the abovementioned subject area. The thesis will be assigned and carried out in accordance with the rules of your university. For this reason please discuss the thesis with a professor who can advise you over the course of the project.
We value and promote the diversity of our employees skills and therefore welcome all applications regardless of age gender nationality ethnic and social origin religion ideology disability sexual orientation and identity.
Apply online now (PDF: cover letter CV transcripts). We look forward to getting to know you!
Anne Weber
FraunhoferInstitute for Integrated Circuits IIS
Experience:
Unclear Seniority
Employment Type
Full-Time
Key Skills
Similar Jobs
Dr. Job is an online platform that connects employers with skilled job seekers, facilitating the search for job opportunities and top talent. Established in 2015. Dr. Job Pro has emerged as the world premier job portal, attracting thousands of job seekers every day from all over the world.
Follow Dr.Job
Dr Job FZ LLC. 2025 © All Rights Reserved