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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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Applied ScientistWhy We Have This RoleWe are looking for talented and innovative Applied Scientist to bring our Machine Learning and Artificial Intelligence R&D and strategy to the next level.
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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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Relevant certifications such as Microsoft Certified: Azure Data Scientist Associate or AWS Certified Machine Learning are advantageous. Python ecosystem preferred, R will be acceptable, machine learning libraries & frameworks (e.g. TensorFlow, PyTorch, scikit-learn) and familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI.
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Methods vary widely but include applied mathematics, deep learning, machine learning, probability modeling, Bayesian reasoning, quantum computing, spatial statistics, spatio-temporal modeling, decision support, and data mining.
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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 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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The Computational Biology group in the Clinical Biomarkers & Diagnostics (CBD) department at is seeking a highly motivated Sr data scientist to join our team and contribute to develop machine learning modeling and prediction pipelines using multi-modal biomarker data from clinical trials.
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At Prescient Design, we are seeking a highly motivated Machine Learning Scientist to help drive research on Machine Learning for Drug Discovery. You will be fluent in Python and experience with scientific software development for biochemical modeling (e.g. RDKit, Biopython, MDAnalysis, OpenMM)You will have demonstrated experience with modern Python frameworks for deep learning like PyTorchYou will have experience working with biochemical or biophysical datasets including graph, sequence, and structure-based data.
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Advanced knowledge of cloud computing technologies such as: Apache Spark, Azure Data Factory, Azure DevOps, Azure ML (Machine Learning), Hadoop, Microsoft Azure, Databricks, AWS, Google Cloud.
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If you are a self-motivated data scientist with a passion for bioinformatics and machine learning, and you're ready to take on new challenges, we want to hear from you! Significant experience in bioinformatics, applied mathematics and/or statistics to analyze multi-modal, multi-dimensional and large-scale biological datasets including whole exome sequencing, RNseq, and high-throughput proteomics data.
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An advanced degree (master’s or doctoral) in a quantitative field, including but not limited to Computational Biology, Computer Science, Data Science, Applied Mathematics/Statistics, all relevant engineering and science disciplines.
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Stay abreast of latest AI trends and maintain state-of-the-art knowledge in machine learning, deep learning, and computational linguistics. Experience with machine learning techniques and tools including deep learning, reinforcement learning, and unsupervised learning.
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Requirements: Requires a Master’s in Statistics, Computer Science, Data Science, Machine Learning, Applied Math, Operations Research, Economics, or a related field plus two (2) years of experience as a Data Scientist, Data Engineer, or other occupation/position/job title involving research and data analysis.
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