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Job Description MIT Lincoln Laboratory seeks a highly motivated, detail-oriented, curious and driven physicist, applied physicist, or researcher in a related field with hands-on lab experience.
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PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields. LLM PhD focus on NLP or Masters with 5 years of industrial NLP research experience Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization) Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) Publications in deep learning theory Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR.
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Hands-on experience in handling, processing, integrating, and analyzing large heterogenous biological data sets related to industrial drug discovery research (e.g., sc/snRNAseq, ATAC-seq, genomics, proteomics, etc.
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Current faculty interests are in applied mathematics and computational science in biological, earth science, engineering and physical contexts, and, especially, in biophysics, multiscale fluid mechanics, machine learning, medicine, neuroscience and soft materials.
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This individual will apply their skills in machine learning, image processing, computer vision, mathematics, optics, and software engineering to develop algorithms to be integrated into onto’s innovative inspection platforms.
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FL94 is seeking a hands-on,n experienced, creative, and visionary Machine Learning Lead. Build and lead the data science team translating small molecule and proteomic drug discovery challenges into breakthroughs via deep learning applied to computational chemistry.
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Hands on experience in SAP IBP time series and order-based planning data models. Compare supply availability data such as open POs, On-Hand, WIP and Sales orders between source systems and Planning systems to ensure data is complete and accurate.
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Earned Ph. D. degree in clinical pharmacology, pharmacokinetics, pharmacometrics, mathematics, engineering, computational biology or a related field required, with or without post-doctoral experience plus 5 years of relevant experience.
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Hands-on experience with data monitoring and vendor operations, data collection, data-entry, data-monitoring, data-validation, discrepancy management, data-extraction, and IRB/regulatory requirements.
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But none of these work unless we have participants who are willing to answer questions, join focus group zoom meetings or even test products hands-on and provide feedback. Based on experience, this position pays up to $34.00 per hour.
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Bachelor's degree in Computer Science, Applied Mathematics/ Data Sciences/ Data Analytics or related discipline required, advanced degree preferred. Experience with analytic methods and technologies (artificial intelligence, machine learning/ deep learning/ neural networks, natural language processing, visualizations.
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Every day we open minds through next-gen digital learning and extinguish fear through hands-on education experiences. Focused on delivering an emotional, entertaining, and informative hands-on concealed carry training experience, Concealed Coalition has changed the game in "on the ground" localized CCW certification.
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The Role:The Cambridge Rindge and Latin School, in partnership with the Health and Physical Education department, seeks a Health Education Teacher for the 24-25 School Year. The teacher will report directly to the Coordinator of Health, Physical Education and Wellness and to the principal of the school or small learning community administrator to which she is assigned, as well as to the CRLS PE/Health Lead Teacher.
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We are looking for a self-directed professional to support Digital Health Technology [DHT] (wearable sensors) and imaging components set-up and monitoring within clinical trials; specifically focused on the operational initiation/set-up, vendor and digital data/imaging monitoring, and data cleaning process efforts that occur within the Biomeasures Endpoints and Study Technologies (BEST) projects.
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Lead the development, implementation, and operations of HR software systems, including Workday, SAP Success Factors Learning Management System, Veeva Learning, Tableau analytics, and AWS-based data analytics and repository layer.
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