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Field
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of heterogeneous technologies are increasing the complexity of power delivery, thermal management, and energy optimization across the entire computing stack. Emerging technologies such as fine-grain 3D integration
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methods and GIS tools to create 3D environments that integrate high-resolution 3D urban models with climate-resilience objectives. This should help policymakers and citizens optimize energy-efficiency
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peptidomics at Lund University. The duties include: Planning and conducting experiments. Developing and optimizing methods for sample preparation, peptide enrichment, and fractionation. Performing LC-MS/MS
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International Centre for Translational Eye Research / Institute of Physical Chemistry, Polish Academy of Sciences | Poland | 29 days ago
will assist the micromanipulation of the injection device with 3-D localized imaging. Further information on the research priorities and current expertise of our Center can be found at http
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studies investigating target-directed microRNA degradation (TDMD) in T-cell acute lymphoblastic leukemia Establish, optimize, and maintain T-ALL experimental systems, including cell line, primary patient
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of software infrastructure to optimize data workflows Developing analytical methods to integrate different types of sequencing-based DNA data. Developing computational models for prognosis and treatment
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Job description The Discrete Mathematics and Optimization group within the Delft Institute of Applied Mathematics at TU Delft is offering a full-time PhD position in the area of combinatorics
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16th August 2026 Languages English English English The Department of Industrial Economics and Technology Management has a vacancy for a PhD Candidate position: Hybrid AI-Optimization for Dynamic and
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optimization of these building blocks are essential for achieving breakthroughs in data rate, power efficiency, scalability, and overall system cost. This PhD project focuses on the electronic integrated circuit
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-constrained devices such as wearables, smart sensors, hearables, and IoT nodes. While current deployment methodologies can optimize models before deployment, the resulting software remains static throughout