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researcher position with an anticipated duration of 16 months, to work under the direction of Dr. Melissa Lucash. In our lab, we use a variety of tools (e.g. big data, spatially explicit simulation modeling
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team are required. Preferred Qualifications Candidates with pulmonary research experience are preferred. Experience in understanding big data analysis (RNAseq, mass spec/phosphoproteomic analysis, etc
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and sets up experiments in hybrid research environment. 2. Researches artificial intelligence/machine learning algorithms, database design, deep learning, big data, and cloud computing. 3. Publishes
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language processing), machine learning, or data science. Preferred Qualifications Expertise in Deep Learning and LLMs(Large Language Models): Knowledge in building applications and fine-tuning models like Llama 3
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required Working knowledge of all aspects of planning and deploying an AI project, including initial problem specification, data gathering and analysis, model creation, and implementation Strong
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on hotspot detection. This modeling work is well supported by large-scale primary datasets, including survey-based, parasitological, serologic, and genomic data. Relevant methodologies include mechanistic
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driven individual with a PhD in data science, computer science, biomedical informatics, or a similar background with some experience working with large datasets. Prior experience with healthcare is not
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, though exceptional candidates with expertise in human cognitive neuroscience are encouraged to apply. Position Overview Successful candidates will lead projects involving: • Large-scale neurophysiology
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information Ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork Desired skills, knowledge and abilities: Experience with large-scale molecular dynamics (MD) simulations
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Missouri University of Science and Technology | Rolla, Missouri | United States | about 19 hours ago
will be evaluated on: • Prior knowledge and demonstrated expertise in next-generation sequencing data analysis, computational systems biology, and/or data integration; • The ability