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Experience in mathematics (statistics, linear algebra, differential calculus); data visualization (Tableau, Power BI, Qlikview); programming (SQL, Python, R, Java); data analysis (feature engineering, data wrangling, EDA) and machine learning (classification, regression, reinforcement learning, deep learning, clustering, dimensionality reduction.
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We are seeking a machine learning engineer to work closely with our product and research teams to develop SOTA deep learning software. Solid knowledge of machine learning and deep learning fundamentals with experience in one or more of computer vision, NLP, speech, reinforcement learning, generative models, etc.
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Should have a strong background in at least one of the following areas: Algorithm Development, Machine Learning/AI and Data Analysis, Mathematical Modeling and Simulation, Digital Signal Processing, Control Algorithms Design.
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There are various disciplines involved in Enterprise Data & Analytics, including: data source identification and analysis, data engineering, data visualization & data science/machine learning.
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The centerpiece of this initiative is the establishment of a "ML Research Hub," a new group charged with mastering state-of-the-art machine learning techniques to create novel predictive models and tools used across WRDM. Data Engineering will be key to the success of this new group given the enormous scope of the chemical, biological, omics, and clinical data available at Pfizer.
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Extensive experience with AI, Machine Learning, Machine Learning Ops, Data Engineering, or Data Science. WillowTree, a TELUS International Company, partners with the world's leading brands to help them tackle their thorniest challenges - be it launching new digital products, delivering personalized marketing at scale, or harnessing the power of data and AI to transform their business.
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The successful candidate will bring experience as a data scientist and machine learning leader working for a company where "AI" is considered core to the company's success. Serve as a strategic leader as part of our data science & machine learning team, with responsibility for Xometry's pricing strategy.
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The Senior Lead Data will be responsible for partnering with Technology, Machine Learning, Product Architecture, and other Capital One teams to support the development of the Finance Tech Data Strategy into products and services we create and consume.
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CPD is seeking a computational scientist specialized in machine learning to join our team. ( Responsibilities Develop machine learning (ML) methods to predict complex structures induced by molecular gluesDevelop and integrate generative AI algorithms for the design of small molecular glues Support the small molecule drug discovery projects at CPD using advanced ML methodsWork with leadership team to develop project proposals, timelines, and resource requirements.
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Strong familiarity with topics of protein and macromolecular structures and interactions with other proteinsExperience with cloud environments such as AWSExperience in developing machine learning platforms using modern ML frameworks for deep learning (, tensorflow, keras, MXNet) & deploying in services such as Amazon Sagemaker.
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Expected Qualifications: Demonstrated knowledge and teaching experience in at least one of the following areas: Statistics, Data Analytics, Data Visualization with different tools, Python, Data Management & SQL, Data Engineering, R Programming, and/or Machine Learning.
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Collaborate effectively with renowned GSK experts in genetics, genomics, computational bio & chem, structural biology and medicinal chemistry, artificial intelligence / machine learning, and digital technologies to build the datasets, tools, models, and infrastructure necessary for oligo design & development.
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You will apply your skills in machine learning and data engineering on complex multi-omics and preclinical datasets. Primary Responsibilities Include: Implementation of computational methods and data engineering for omics data sets such as Next Generation Sequencing (NGS.
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We are seeking a highly motivated machine learning and AI Principal Scientist to join our Computational Tissue Imaging Research team in the Translational Bioinformatics organization. Strong coding skills in Python, and experience with machine-learning and deep learning libraries (e.g., Scikit-learn, TensorFlow, PyTorch, etc.
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Significant relevant experience after your MD/PhD/postdoc including quantitative expertise in biostatistics, bioinformatics, computer biology, statistical genetics, clinical imaging, machine learning, or data science; interpreting and publishing studies consisting of "omics" data e.g. genetics, genomics, proteomics; closely partnering with/leading data scientists.
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