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Posting Title Graduate PhD Student Intern (Summer) – Mathematical Optimization . Location CO - Golden . Position Type Intern (Fixed Term) . Hours Per Week 40 . Working at NLR NLR is located
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on the distribution grid with distributed energy resources (DERs). The intern will work on projects developing learning-based analytics, and cyber-attack-resilient control strategies and optimizations for power
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conditions for a rewarding career. Job Summary The Aparicio lab is developing new single-cell genome and transcriptome methods for tracking clonal trajectories at the single-cell level in patient tissues and
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-time, large-scale data demands of IIoT and lack sustainability considerations, such as energy efficiency. This research proposes a sustainable, high-performance IDS that leverages digital twin technology
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Infrastructure? No Offer Description Area of research: PHD Thesis Job description: Your Job: Energy systems engineering heavily relies on efficient numerical algorithms. In this HDS-LEE project, we will use
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of scientists and researchers in an effort to research transcription factor-based sensors for waterborne toxins of interest. High-throughput cell-based and cell-free screening approaches, along with
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professional goals. Along the way, you will engage in activities and research in several domains. Available topical areas include, but are not limited to: Optimization Reinforcement learning Bayesian analysis
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Your Job: Energy systems engineering heavily relies on efficient numerical algorithms. In this HDS-LEE project, we will use machine learning (ML) along with data from previously solved problem
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to ensure optimal performance and result accuracy. Strong willingness to learn and apply skills learned on the job in utilizing telemanipulators, specialized hot cell functioning, and essential QA/QC
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efficient model parallel training Implementation and optimization of GPU-accelerated training pipelines Validation of models on patient-specific geometries obtained from MRI data Participation in conferences