Responsibilities:Develop and implement algorithms for sleep staging using biosensor dataImplement sensor fusion algorithms for integrating multi-modal dataDesign and optimize pipelines for extracting features from physiological signalsCreate models for analyzing and predicting sleep patternsDevelop real-time systems for optimizing sleepDesign and validate control systems for intervening in sleep patternsMaintain documentation for algorithms and modelsCollaborate with hardware and software teams on product developmentRequirements:Master's or PhD in relevant field such as ML, Signal Processing, or Biomedical EngineeringSolid understanding of signal processing and time series analysisExperience with processing biomedical signals like EEG and PPGProficiency in Python and ML frameworks like PyTorch and TensorFlowExperience with deep learning architectures like RNN and LSTMKnowledge of biosignal analysis including HR/HRV and sleep stagingStrong mathematical background in modeling and control systemsPreferred Skills:At least 4 years of experience in biosignal processing or sleep researchExperience in developing product with real-time signal processing systemsKnowledge of Edge Computing and Embedded ML deployment (TinyML)Background in Closed-loop control systemsPublished work in relevant fields such as Biosignal processing and Sleep ScienceSalary and Benefits:Competitive salary Opportunities for professional development and networking in wearable technology and researchChance to work on cutting-edge technology in the rapidly growing sleep tech marketPotential for significant impact in a high-growth startup environmentCollaboration with world experts in sleep, neuroscience, AI, and wearablesVisa application support for international candidates recblid 3sxd2ioo8gc678gjbe4irwcfmt0dbf