Computational Neuroscientist / Machine Learning Scientist
Santa Clara Valley (Cupertino), California, United States
Machine Learning and AI
At Apple, we strive to achieve surprise and delight for every one of our millions of customers around the world. The Technology Development Group is currently looking for a computational neuroscientist who is passionate about building advanced algorithms for performing inference on complex neural and physiological signals. You will have a strong research background and have made original contributions to both basic science and to the development of novel data analytical methods. You are an expert in navigating large and noisy data sets, embrace uncertainty, and have a strong foundation in machine learning and numerical computing. You are a great teammate with excellent interpersonal skills, and have a dedication to conducting impactful research in support of neurotechnology development.
- PhD in Computational Neuroscience, Biomedical Engineering, Applied Mathematics, or related field.
- Strong theoretical and applied background in some or all of the following: neural networks, unsupervised/supervised learning, sensor fusion, neural coding, optimization theory, information theory, and control and dynamical systems.
- Experience in statistical and signal processing, linear algebra, time-frequency analysis and their application to multivariate neurophysiological and neuroimaging datasets.
- Fluency in a high-level programming language (Matlab and/or Python) and experience with ML tools (scikit-learn, pandas and deep learning toolboxes such as TensorFlow, PyTorch, Caffe, etc.)
- Research experience carrying out data driven algorithm design and translating exploratory data analyses into robust ‘decoding’ models.
- Excellent programming, problem solving and debugging skills
This is a multi-faceted scientific role that will require you to be versatile across a variety of tasks in a highly collaborative environment. You will work closely with other scientists and engineers to rapidly carry out studies that help drive research and development. You will have the following responsibilities: You will carry out extensive analytics that aim to pull out meaningful and actionable insights from complex multimodal datasets You will harness your insights to design multimodal inference algorithms. You will help to architect and port real-time algorithms to a variety of platforms. You will build analytical tools that will be used by other members of a cross-functional team.
Education & Experience
PhD in Computational Neuroscience, Biomedical Engineering, Applied Mathematics, or related field.
- Postdoctoral and/or industry research experience.
- Hands-on experience with convolutional networks and recurrent neural networks (LSTMs, GRUs and etc.).
- Hardware and software experience with multimodal data acquisition, instrumentation, and human-machine interfaces.
- Knowledge of perceptual/behavioral evaluations and physiological measurements.
- Prototyping experience.