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We are on the forefront of CBRN defense and we are looking for talented Data Scientists that have applied experience in the fields of artificial intelligence, machine learning and/or natural language processing to join our team.
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Java, Python, ScalaExperience in Natural Language Understanding, Computer Vision, Machine Learning, Algorithmic Foundations of Optimization, Data Mining or Machine Intelligence (Artificial Intelligence.
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The Research Data Scientist participates in biomedical research projects using programming, data-mining, statistics, machine learning, and visualization techniques to develop, evaluate, and/or apply algorithms and software for data analysis.
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Solid ML background and familiar with standard NLU, NLG, and LLM techniquesPREFERRED QUALIFICATIONS- PhD in Computer Sciences, Electrical Engineering, or Mathematics with specialization in machine learning, deep learning, or natural language processing- 4+ years experience in building conversational AI and/or natural language processing systems.
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Basic to substantial experience in one or more of the following commercial/open-source data discovery/analysis platforms: RStudio, Spark, KNIME, RapidMiner, Alteryx, Dataiku, H2O, SAS Enterprise Miner (SAS EM) and/or SAS Visual Data Mining and Machine Learning, Microsoft AzureML, IBM Watson Studio or SPSS Modeler, Amazon SageMaker, Google Cloud ML, SAP Predictive Analytics.
$135,240 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Basic knowledge and experience in statistical and data mining techniques such as: generalized linear model (GLM)/regression, random forest, boosting, trees, text mining, hierarchical clustering, deep learning, convolutional neural network (CNN), recurrent neural network (RNN), T-distributed Stochastic Neighbor Embedding (t-SNE), graph analysis, etc.
$135,240 a yearFull-timeExpandApply NowActive JobUpdated 17 days ago - UpvoteDownvoteShare Job
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Stay up-to-date with the latest advancements in data science, machine learning, and related fields, and apply them to improve existing processes and methodologies. Apply various Machine Learning (ML) and analytics techniques to develop classification and prediction models and leverage foundation models to develop generative AI capabilities; integrate client, domain (e.g., finance, sales) and industry knowledge into the solution.
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Bachelor's or Master's degree in a quantitative field such as Computer Science, Data Engineering or related discipline. Experience with data visualization tools and techniques to effectively communicate insights and findings.
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Requirements: Bachelor's or Master's degree in a quantitative field such as Computer Science, Data Engineering or related discipline. Sourcing and Spent OptimizationThe Role:You will help our clients navigate the complex world of modern AI, data science and analytics.
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Proficiency in programming languages such as Python, R, or SQL. Strong knowledge of machine learning techniques, statistical analysis, and data visualization tools Tableau, Power BI.
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We work alongside product teams across MI ES on break-through ideas using tools and techniques spanning the entire spectrum of Data Science, Statistics, Machine Learning, Deep Learning, NLP, Gen AI, Operations Research, Data and Machine Learning Engineering.
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Qualifications We DesireMaster’s degree in Computational Biology, Computational Bioengineering, Machine Learning, Statistics, Computer Science, Mathematics, or a related field. Knowledge and experience developing and applying algorithms in one or more of the following machine learning areas/tasks: deep learning, unsupervised feature learning, zero- or few-shot learning, active learning, transformer-based language modeling, multimodal learning, ensemble methods.
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Deep knowledge in Machine Learning, Deep Learning, Data Mining, Information Retrieval, Statistics. Applied AI ML opportunities are available at the VP level for our Quant AI team within the Machine Learning Center of Excellence.
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Argonne’s Leadership Computing Facility (ALCF) and Mathematics and Computer Science Division (MCS) is looking for a Postdoctoral appointee working at the intersection of scientific machine learning SciML and large-scale simulation codes.
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You will deploy and deliver technical solutions at the intersection of computational chemistry and machine learning, supporting research directions in molecular design across broader gRED and Roche.
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