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We seek a collaborative and highly innovative computational scientist to join our Predictive Sciences team and develop predictive models using cutting-edge machine learning/artificial intelligence techniques to discover novel therapeutic opportunities.
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As a Machine Learning Engineer, you'd be joining a talented and friendly team which loves to delight its customers with quality and robust code. Use off-the-shelf machine learning solution to provide simple initial solutions for fraud detection.
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MBRDNA is headquartered in Silicon Valley, California, with key areas of Autonomous Driving, Advanced Interaction Design, Digital User Experience, Machine Learning, Customer Research, and Open Innovation.
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We are seeking a highly-skilled and experienced Senior Machine Learning Scientist to join us and help advance our current and future work applying machine learning, deep learning, and NLP to deliver better health care.
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This work will be performed in close collaboration with pediatric neurologist and epileptologist clinician researchers and faculty at NCH.The candidate should be able to leverage both structured and unstructured data sets to create analytical solutions using tools and/or methods in at least one of the following areas: statistical and predictive modeling, machine learning, natural language processing, and geospatial analysis.
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Specialized training in Data Engineering, Data Science, Machine Learning, Big Data Platforms (Spark, Kafka, Hadoop, H2O, etc.) LICENSING/CERTIFICATION Any certification specializing in data engineering, big data, data science, machine learning, artificial intelligence, or statistical analysis from accredited institutions of higher learning.
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As a Machine Operator (SDS Operator Trainee) with Tradebe, you will assist with the operations of the Solids Distillation System (SDS) and the operations of the Distillation Column during a one year training and learning period.
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If you have a solid foundation in machine learning and a keen interest in peptide/protein engineering and design, you could be pivotal in our journey. Your foundation in machine learning, combined with an interest in peptide/protein design, is what we value.
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The selected candidate will apply plasma physics simulations of the tokamak core and pedestal using high performance computing resources and machine learning accelerated architecture. Machine learning techniques and statistical methods will be leveraged to build fast surrogate models that accelerate predictions of tokamak plasma scenarios.
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This team is a cross-functional group of exceptional biologists, engineers, product managers, machine learning scientists, computational biologists, and data scientists. Recursion leverages sophisticated machine-learning algorithms to distill from its dataset a collection of trillions of searchable relationships across biology and chemistry unconstrained by human bias.
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We are looking for a passionate, talented, and resourceful Senior Applied Scientist in the field of LLM, Artificial Intelligence (AI), Natural Language Processing (NLP), Recommender Systems and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware conversational AI. A successful candidate will have a strong machine learning background and a desire to push the envelope in one or more of the above areas.
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Proficiency in Google Cloud Platform (GCP) services relevant to machine learning and AI, such as AI Platform, BigQuery, Dataflow, and Tensorflow. Master’s Degree in related field (e.g., Data Science, Predictive Analytics, Machine Learning, Statistics, Applied Mathematics, Computer Science.
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NVIDIA is building the world’s leading AI company, and we are looking for an experienced Cloud Solution Architect to help assist customers with adoption of GPU hardware and Software, as well as building and deploying Machine Learning (ML) , Deep Learning (DL), data analytics solutions on various Cloud Computing Platforms.
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Strong understanding of machine learning algorithms, techniques, and frameworks, including deep learning, neural networks, and ensemble methods. Experience with building and training machine learning models using tools like TensorFlow, Keras, or PyTorch.
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Understanding of containerization technologies like Docker for packaging machine learning models and deploying them in production. Ability to design and implement end-to-end machine learning pipelines for data ingestion, processing, modeling, and deployment.
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machine learning jobs Title: principal Company: Spectrum
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