49 biogeochemical-modeling PhD positions at Technical University of Denmark in Denmark
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functional priors from billions of years of evolution; how to compress measurements with controlled mixtures of molecules; and how to align models of laboratory experiments with observational human biology
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College Dublin, Ireland and Northeastern University, USA. Responsibilities The PhD project involves developing a flexible vegetation model within the OpenFOAM platform, where vegetation stems
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, or biophysics. Experience with experimental organic chemistry, NMR, kinetic modelling and/or cheminformatics are advantages. The candidate must be able to work independently, but also participate in
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nanoparticles and reactions at the atomic-level by combining path-breaking advances in electron microscopy, microfabricated nanoreactors, nanoparticle synthesis and computational modelling. The radical new
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with colleagues at DTU and IIT Bombay, as well as with academic and industrial partners globally. The main purpose of this PhD position is to develop, implement and assess machine learning models
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(ORR), oxygen evolution reaction (OER), and carbon dioxide (CO₂) reduction. Collaborating with theoretical research groups to guide the design of active site structures through computational modelling
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background in Computer Science, Informatics Engineering, Mathematical Modeling, Computational Urban Science, Transport Modeling or equivalent, or a similar degree with an academic level equivalent to a two
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products under different operating conditions. Testing new bioreactor configuration for carbon dioxide biological conversion. Modelling carbon dioxide fermentation to acetic acid. Contribute as teaching
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intelligence. This PhD project will leverage the power of field-programmable gate arrays (FPGA) to deploy machine learning models on the edge with low latency and high energy efficiency. This added intelligence
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an efficient AI foundational exploration of the molecular space. How can we bias the generative models towards desirable molecular properties How can we integrate generative AI models and different molecular