We work across the whole stack when it comes to the design and conception of a neuromorphic chip, from the Neuromorphic Algorithms focused on continual learning to the processor design and mixed signals circuit design for the acceleration of such algorithms. We focus on low power applications particularly on gesture recognition and computer vision for robotics/drones. Our goal is to give the opportunity to our members to do amazing research and possibly publish their work.

We are looking for: (no need to cover all points as we have subdivisions within this team)
‍- Knowledge on computer architecture.
- Knowledge on RISC-V.
- Knowledge on Machine Learning framework (pytorch, tensorflow).
- Knowledge on Computational Neuroscience.
- Knowledge on Analog/Digital design.
- Excitement on on our mission and goal.
- Open mentality and be team driven.
‍
Projects available:
- RISC-V Processor Design for Controlling SNN Accelerator.
- SNN AI Compiler (TVM) and low dependency SNN in C.
- Mixed-Signal Design (Analog & Digital) for Crossbar array and Event-Based Camera
- Learning Rules for continual learning.
- Applications: Gesture recognition — Robotics — Drones

PD.: If you are interested in Neuromorphic Computing Applications, we recommend you to apply to the Neuromorphic Hackathon 2024! You can find more information in the nav tab.

We are all about public image and science communication. In this subteam we create posts and short form videos for social media, write blogposts summarizing scientific findings or club activities and plan neurotechnology events with renowned Professors. Another big part is networking and ensuring funds for the rest of our initiative, as well as designing our beloved merch.

We are looking for:
- People excited about networking and talking to companies.
- Graphic design knowlegde and experience.
- Interest in science communication towards a general audience.
- General motivation and interest in the field of neuroscience.

Tasks:
- Create Instagram and LinkedIn Posts.
- Write Blogposts about events and interesting papers.
- Talk to companies and manage sponsoring possibilities.
- Event planning.

This is some text inside of a div block.We are an interdisciplinary group of students at the intersection of Engineering and Neuroscience. With this group, we hope to enable students of every background to dive into the fascinating world of neurotechnology. To achieve this, we need a reliable and structured organization that enables us to receive funding, create collaborations, and reliably conduct work within our groups. This is where you step in.

We are looking for:
- Knowledge of German laws or experience working within the German legal system.
- Experience in accounting and financial planning.
- Experience in managing IT and Project Management systems.
- Interest in running a non-profit organization and learning all of the above.

Tasks:
- Setting up the club's working infrastructure (Notion, Google Drive, Discord, Storage, etc.)
- Handling all the legal and ethical matters of the club (Drafting up contracts and legal documents, Privacy/Data Policy, etc.)
- Handling the club’s finances and working on its strategic development.

Disclaimer: If you are interested to help us plan the future of this group after the Cybathlon please still reach out to us through email. We will get back to you at the start of November.

Within this group we are working on developing a brain-computer interface. By collecting EEG signals, processing them, and classifying them, we could offer quadriplegic people the possibility of controlling virtual environments (e.g. Mouse cursor on a screen) with only their brains. We envision this to then be translated into the real world into a project such as a mind-controlled wheelchair or robotic arm. This team consists of different sub-teams that work together to put the different pieces of the BCI together. The first milestone of this team is the participation in the ETH Cybathlon 2024 - BCI race.

We are looking for:
- Excitement about the field of assistive technologies and neurotechnology.
- Hands-on experience with Machine Learning and Deep Learning (preferably in PyTorch).
- Hands-on experience processing EEG signals (working with EEG data, preferably in mne-python).
- Knowledge of neuroscience and conduction of EEG experiments.
- Motivation and Interest to learn all of the above.

Tasks:
- Work on applying and developing deep learning methods to classify signals from EEG data.
- Process EEG data by filtering out artifacts (e.g. eye movement), removing noise, and extracting the necessary features for our controller.
- Help design and conduct EEG experiments that aim to enable our pilot to train to play the game for the Cybathlon competition.
- Develop a complete BCI that can reliably classify 5 different classes.

Our job is to design and build various pieces of electronic hardware for the club. Our current project is to build our own EEG from scratch. We’ve made good progress and are already looking at new project ideas which include working together with the Brain-Inspired Computing team on prosthetics or robotics.

We are looking for:
- Knowledge about digital circuits, PCB design, and soon robotics and control systems
- Interest in working in a team, often in-person - this point is strictly required :)
- Ideally experience with the above
- Ability to withstand some frustration ;)

Tasks:
- Read documentation, datasheets, and other requirements
- Design custom PCBs using KiCAD
- Solder SMT components to said PCBs
- Interface microcontrollers or Raspberry Pis with the PCBs and program them
- Inevitably debug mistakes in software and hardware with the help of oscilloscopes

We are developing an algorithm aiming to map a potential rare disease (ICD10 code) / rare disease type (limited to neurological diseases for the time being) to help inform treatments for affected children. We plan to train deep learning models using a variety of data sources, including multiomics data, presented in a graph format.

We are looking for:
- Interest and knowledge about bioinformatics or similar.
- Hands-on experience with deep/ machine learning (Python).
- Ideally experience with graph-neural networks.

Tasks:
- Proof-of concept with dummy dataset.
- ⁠Hands-on work with graph neural networks.