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PhD and 2+ years of relevant research experience in developing machine/deep learning-based solutions and a sincere interest for computational life sciences. The ideal candidate should have an outstanding scientific reputation in the field of machine learning research for computational biology and a demonstrated passion for solving biological problems relevant to drug discovery.
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Advances in bigchemical data, massive computing power, artificial intelligence, andmolecular dynamics simulation are changing the way we develop newdrugs.
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The Machine Learning Motion Planning team specializes in the fusion of Machine Learning and Classical Methods, researches and develops new heuristic and deep learning approaches, and builds deep neural networks, algorithms, and software to make an impact across navigation, behavior, route planning, as well as trajectory optimization, numerical optimization, and model predictive control.
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Experience with analytic methods and technologies (artificial intelligence, machine learning/ deep learning/ neural networks, natural language processing, visualizations) Demonstrated proficiency with data science languages (R, Python, SQL, Julia, SAS) and visualization tools (Tableau, Spotfire, SAS, JMP, RShiny.
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The ideal candidate will bring experience in molecular modeling of proteins and protein complexes, structure-based design tools, and state-of-the-art deep learning approaches, helping us unlock the potential of molecular mimicry for therapeutics development.
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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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Deep knowledge of machine learning, both theory and application. 5+ years of experience in data analysis or data science, with 3+ years focusing on machine learning problems, ideally in a relevant space (KYC, sanctions detection, anti-fraud detection, treasury management, crypto/blockchain data science.
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Knowledge of NLP libraries, ontology-based and deep learning-based libraries, (i.e., Huggingface, SpaCy, NLTK, cTAKES, MetaMap, or John Snow Labs) The Lead Data Science and Machine Learning (ML) executes Ontada’s technology roadmaps in ML and Natural Language Processing (NLP) Data Platform roadmap through close collaboration with Ontada commercial, chart abstraction and engineering teams.
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Experience with machine learning tasks such as natural language processing, image recognition, semantic segmentation, reinforcement learning, approaches such as Bayesian, deep convolutional and graph neural network methods, and tools such as PyTorch, Ray, TensorFlow/board, and MLflow.
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You will be part of the AI team at VideaHealth, where you will closely work within the team of Machine Learning engineers on a well defined project that is focused, dependent on the candidate, around Deep Learning or Data Science.
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Familiarity with AI (Artificial Intelligence) subsets such as Machine Learning, Large Language Models (LLM) and Natural Language Processing (NLP). Deep knowledge and experience of managing, orchestrating, and monitoring distributed production systems.
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A first-of-its-kind 3.0 Tesla MRI with ultrafast MR imaging informed by deep learning (AI) reconstructions, an additional 3.0 Tesla magnet, and a new 1.5 Tesla MR. The world of healthcare is changing fast and Commonwealth Radiology Associates is the “tip of the spear” when talking about advancements in Diagnostic Modalities, Image-Guided Intervention, AI, Machine Learning, and Health Blockchain Technology.
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Experience using Deep Learning frameworks such as PyTorch, Tensorflow and/or Jax. Collaborate with other researchers and experts to develop machine-learning methods for problems in computational biology.
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Drive cross-functional collaboration across our data science, machine learning, lab informatics, and medicinal chemistry teams to advance our computational infrastructure for our drug discovery and development mission.
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We are currently sourcing for a Lead Software Engineer, Machine Learning to work at Fidelity Investments. As a Machine Learning Engineer, build and maintain large scale ML Infrastructure and ML pipelines.
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machine learning deep jobs Company: Services Llc in Boston, MA
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