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Data science, machine learning, optimization models, Master's degree in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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Have expertise in Machine Learning best practices (e.g. model evaluation and hyperparameter tuning, A/B test, feature engineering, feature/model selection), algorithms (e.g. gradient boosted trees, neural networks/deep learning, optimization) and domains (e.g. natural language processing, computer vision, personalization and recommendation, anomaly detection.
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Stay informed and integrate latest statistical modelling, machine learning, deep learning, recommender system and/or artificial intelligence trends to improve and enhance modelling stack and improve business metrics and customer experience.
$136,000 - $200,000 a yearFull-timeExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Bring your passion about improving healthcare with your experience in developing image analysis tools, training machine learning models, and deploying software in a commercial setting. Collaborate and in some cases coordinate research efforts with scientists and engineers to develop new algorithms and software for the analysis of single molecule fluorescence data.
$127,000 - $174,700 a yearFull-timeExpandApply NowActive JobUpdated 3 months ago - UpvoteDownvoteShare Job
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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 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.
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Fx, XLA and MLIR; - Large scale data processing and parallel computing; - Experiences in designing and operating large scale systems in cloud computing or machine learning; - Experiences in in-depth CUDA programming and performance tuning (cutlass, triton) Preferred Qualifications Graduating December 2024 onwards with the intent to return to degree program after the completion of the internship.
$57 a yearInternExpandApply NowActive JobUpdated 3 months ago - UpvoteDownvoteShare Job
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The Clinical Data Science team at Eisai, Inc., is expanding its capabilities by acquiring in-house talent related to bioinformatics, machine learning, and big data analytics for the Oncology and Neurology clinical programs.
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Have experience applying signal processing, image processing, pattern recognition, machine learning, deep learning, or related techniques with respect to signal extraction from sensors.
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We Are Seeking a Talented And Skilled Machine Learning Scientist II To Join Us And Help Advance Our Current And Future Work Applying Machine Learning, Deep Learning, And NLP To Deliver Better Health Care. We Contribute Broadly Across Cambia, Working On a Wide Range Of Challenging Problems, For Instance.
$110,500 - $180,500 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Demonstrated expertise in statistical theory and a wide range of statistical methods and machine learning techniques for high-dimensional multi-omics data. 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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Derive novel prognostic and predictive signatures using statistical and machine learning methods to guide patient stratification and biomarker selection in clinical trials. Perform integrative analyses of multi-omics data from clinical trials and research cohorts, including genomics, transcriptomics, proteomics, and imaging, to identify biomarkers related to treatment mechanism and response, and potential therapeutic targets.
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Establish, develop, and implement optimal bioinformatics pipelines for the analysis of next-generation sequencing and other -omics data. Collaborate with translational scientists and clinicians to design and execute data analysis strategies that address key clinical oncology research questions.
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Extensive experience and expertise, demonstrated via a strong publication record and prior work experience, in the analysis of cancer genomics data, including whole-genome sequencing, exome sequencing, RNseq, and epigenomic data.
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Ph. D. in Computational Biology, Biostatistics, or a related field. Proficient in programming languages such as Python, R, and Perl, with a mastery of various bioinformatics tools and software, along with experience in developing bioinformatics pipelines.
Full-timeExpandApply NowActive JobUpdated 7 days ago
machine learning jobs Title: sr data scientist Company: Leidos
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