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Employ advanced AI and machine learning models, including deep learning and predictive analytics, to identify novel materials and predict their performance within battery systems.
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A Glimpse into the Daily Routine of a Machine Learning Engineer. Self-motivated and proactive, with a passion for learning and staying updated with the latest trends and advancements in the field of data engineering.
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Individuals in this role are expected to be recognized experts in areas such as artificial intelligence, machine learning, computational statistics, and applied mathematics, particularly including areas such as deep learning, graphical models, reinforcement learning, computer perception, natural language processing and data representation.
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Causal Machine Learning, Causal Inference, Causal Discovery, Counterfactual, Causal Deep Learning, Causal Structure, Structure Learning, Structure Equation Model, SEM, Explainable AI, XAI, Data Science, Deep Learning, R, Python, Julia, Bioinformatics, Multiomics, Integrative Analysis, Medicine, Actigraphy, Pregnancy, Precision Medicine, Personalized Medicine, EHR, Electronic Health Records.
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Machine Learning and Deep Learning: Good understanding of: ML algorithms like linear regression, logistic regression, etc., supervised, unsupervised, and reinforcement learning, AI Frameworks like TensorFlow, PyTorch, scikit-learn etc., Neural network, NLP, computer vision, and predictive analytics.
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Big data/machine learning and AI techniques, including neural network and deep learning frameworks and machine learning tools (e.g., TensorFlow, Theano, Torch, Keras.
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Have functional knowledge related to some of the following: modeling knowledge of financial risks and derivative products (e.g., equity, FX, commodities, credit and interest rates), risk management, model development, model validation, advanced analytics (e.g., machine learning techniques.
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The Knowles and Azizi labs are seeking a joint postdoctoral research scientist with a background in computational biology, machine learning, and statistics, as well as preferably genomics and cancer biology.
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AI and Machine Learning: Utilize state-of-the-art AI and machine learning techniques, including natural language processing (NLP), to train the chatbot for accurate and effective communication.
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As a Lead, Machine Learning Engineer, you will partner with Data Scientists, Data Engineers, Data Analysts and other professionals to implement machine learning models that will deliver stability, producibility, scalability and integration with other products and services.
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Strong proficiency and experience in one or more of the following areas are essential: single-cell genomics, machine learning, multi-variable statistics, open-source software development, or bioinformatics.
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Our client is a pioneer within the programmable RNA medicine space and are looking for an expert of Machine Learning, Artificial Intelligence, and RNA Biology to help shift the paradigm of novel drug development.
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Develop, implement, and optimize machine learning models to detect money laundering, fraud, and other financial crimes, leveraging techniques such as anomaly detection, clustering, and predictive modeling.
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Develop and publish relevant bioinformatics methodologies, pipelines, and algorithms, and stay abreast of the latest advancements in bioinformatics, machine learning, and oncology research.
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Emerging Technologies Group: Covers a wide range of work including Internet of Things (IoT) penetration testing, intelligent automation, artificial intelligence/machine learning and quantum computing.
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machine learning jobs Title: expert Company: Infor in Newark, NJ
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