Culver City, CA /
Machine Learning | Data Science /
Permanent | Full-time
Kernel is building state-of-the-art hardware for acquiring high-quality brain signal data. Our world-class team of neuroscientists, engineers, and physicists have developed hardware that can successfully acquire data non-invasively at a much lower cost and in a much more open environment compared to what is currently available. By overcoming these two major limitations that are currently holding back the progress of understanding the brain, we are able to enable Neuroscience as a Service (NaaS)--neuroscience studies at the touch of a button.
We are looking for an experienced Data Scientist to support the algorithmic development, processing, analysis, visualization, and interpretation of the neural data from our new technologies. The ideal candidate has an intuitive grasp of a rich portfolio of filtering, pre-processing, dimensionality reduction, analysis, and machine learning techniques for various modalities of high-dimensional data. As the data opportunities we face are vast and complex, collaborating effectively with a team on larger projects, as well as digging deep individually, will both be key.
Neuroscience is the new rocket science.
- Rapidly research, implement, validate, and extend processing and analysis algorithms and techniques from the relevant literature
- Generate robust, well-documented, scalable tooling and scaffolding in the process
- Perform data cleaning and assemble usable databases from unstructured data sources and multiple modalities. Bridge across data capture, storage, and processing.
- Implement quality checks and perform targeted analysis on processed data to optimally expose information content
- Build predictive and discriminative machine learning models on large, multi-modal data sets
- Communicate progress, challenges, and results effectively to team members
- Master’s degree in a quantitative field
- 3+ years of industry experience performing advanced signal processing, data analysis, and visualization
- Experience designing and training supervised machine learning models, using both classical ML and contemporary deep learning approaches, on complex, multimodal data
- Understanding of unsupervised learning and reinforcement learning
- Industry-grade coding and software engineering skills. The candidate should be able to write clean, efficient, and well-documented code in python and be familiar with large software projects, version control, as well as tools like numpy, scipy, and matplotlib
- PhD in physics, neuroscience, engineering or related quantitative field
- Strong experience working with time dependent neuroimaging data in particular (EEG, ECoG, MEG, NIRS, fMRI)
- Familiarity with industry-grade data science and infrastructure tools
This position will require access to information protected under U.S. export control laws and regulations, including the International Traffic in Arms Regulations (ITAR) and/or the Export Administration Regulations (EAR). Please note that any offer for employment will be conditioned on authorization to receive software or technology controlled under these U.S. export control laws and regulations without sponsorship for an export license.