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Cég neve
MaxWell Biosystems AG
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Munkavégzés helye
Albisriederstrasse 253, 8047 Zürich -
Munkaidő, foglalkoztatás jellege
- Teljes munkaidő
- Általános munkarend
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Biztosított eszközök
- Linux
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Elvárások
- Nem kell nyelvtudás
- 1-3 év tapasztalat
- Egyetem
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Állás leírása
Responsibilities
Computational Neuroscientist / Electrophysiology Data Analysis Engineer
At MaxWell Biosystems, we innovate the future of electrophysiology by developing cutting-edge technologies for neural activity recording. Our platform includes the software MaxLab Live, a custom-designed integrated circuit, and an FPGA-based data acquisition system that generates vast amounts of data when electrically imaging neu-ronal tissue. These data are processed, analyzed, and visualized in real-time.
We are seeking a highly motivated Computational Neuroscientist or Electrophysiology Data Analysis Engineer to join our interdisciplinary team. The ideal candidate will bridge the gap between software engineering and electrophysiology data analysis, helping us develop novel tools for neuroscience research and drug discovery.
Your Mission
Develop and enhance robust pipelines for neural data analysis, including spike sorting and feature extraction algorithms
Integrate cutting-edge methods, including machine learning or advanced statistical techniques, to improve the accuracy and efficiency of neural data analysis
Collaborate with neuroscientists and electrophysiologists to identify key challenges in data interpretation and implement practical software solutions
Contribute to the development of APIs and tools that simplify and enhance user workflows for neural data exploration
Contribute your own ideas in our agile development process
Work in a multidisciplinary environment, understand customer needs, continuously improve user experience
Our Current Tech Stack
Python – for our analysis algorithms we are relying on the Python data science stack
C++ – for real time processing and visualization
Qt – we embrace Qt for all our user interfaces
Linux and bash
Your Profile
Background in computational neuroscience or electrophysiology with hands-on experience analyzing multi-electrode array (MEA) recordings
Strong understanding of neural spike data, extracellular recordings, and neural signal processing
Knowledge of spike sorting techniques (e.g., SpikeInterface, Kilosort, SpyKING CIRCUS) and neural data anal-ysis workflows is a strong plus
Enjoy writing elegant and maintainable code
Good programming skills in Python, familiarity with C++ is a plus
Experience with LLM-assisted coding tools (e.g. Claude) is a plus.
Knowledge in Linux, Bash and Python
Great teammate, entrepreneurial mindset
Keen to help create a positive, supportive, engaging team environment
Strong interpersonal and communication skills to collaborate effectively with interdisciplinary teams
Why Join Us?
Be part of an international and multidisciplinary team at the forefront of neuroscience and technology
Work on challenging projects that combine biology, computation, and engineering
Help develop cutting-edge tools that advance neuroscience research and drug discovery
Enjoy a collaborative, innovative, and supportive work environment jid36f10adpn jit0311pn jiy26pn
At MaxWell Biosystems, we innovate the future of electrophysiology by developing cutting-edge technologies for neural activity recording. Our platform includes the software MaxLab Live, a custom-designed integrated circuit, and an FPGA-based data acquisition system that generates vast amounts of data when electrically imaging neu-ronal tissue. These data are processed, analyzed, and visualized in real-time.
We are seeking a highly motivated Computational Neuroscientist or Electrophysiology Data Analysis Engineer to join our interdisciplinary team. The ideal candidate will bridge the gap between software engineering and electrophysiology data analysis, helping us develop novel tools for neuroscience research and drug discovery.
Your Mission
Develop and enhance robust pipelines for neural data analysis, including spike sorting and feature extraction algorithms
Integrate cutting-edge methods, including machine learning or advanced statistical techniques, to improve the accuracy and efficiency of neural data analysis
Collaborate with neuroscientists and electrophysiologists to identify key challenges in data interpretation and implement practical software solutions
Contribute to the development of APIs and tools that simplify and enhance user workflows for neural data exploration
Contribute your own ideas in our agile development process
Work in a multidisciplinary environment, understand customer needs, continuously improve user experience
Our Current Tech Stack
Python – for our analysis algorithms we are relying on the Python data science stack
C++ – for real time processing and visualization
Qt – we embrace Qt for all our user interfaces
Linux and bash
Your Profile
Background in computational neuroscience or electrophysiology with hands-on experience analyzing multi-electrode array (MEA) recordings
Strong understanding of neural spike data, extracellular recordings, and neural signal processing
Knowledge of spike sorting techniques (e.g., SpikeInterface, Kilosort, SpyKING CIRCUS) and neural data anal-ysis workflows is a strong plus
Enjoy writing elegant and maintainable code
Good programming skills in Python, familiarity with C++ is a plus
Experience with LLM-assisted coding tools (e.g. Claude) is a plus.
Knowledge in Linux, Bash and Python
Great teammate, entrepreneurial mindset
Keen to help create a positive, supportive, engaging team environment
Strong interpersonal and communication skills to collaborate effectively with interdisciplinary teams
Why Join Us?
Be part of an international and multidisciplinary team at the forefront of neuroscience and technology
Work on challenging projects that combine biology, computation, and engineering
Help develop cutting-edge tools that advance neuroscience research and drug discovery
Enjoy a collaborative, innovative, and supportive work environment jid36f10adpn jit0311pn jiy26pn
How to apply
You can submit your application on the company's website, which you can access by clicking the „Apply on company page“ button.
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