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Field
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, quantum optics is an advantage. General experience of experimental physics is preferred. Experience in data analysis using Python. The outcomes of this project will be disseminated to the scientific
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. Modeling the energy consumption of Smart Cities at different granularity levels (entire city, neighbor- hoods, blocks, buildings). Analyzing and performing benchmark tests on data collected by industrial and
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documents, including OCR post-processing and parsing of legacy texts Proficiency in scientific programming (preferably Python), version control (e.g. Git), and data standards such as RDF and Darwin Core
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: electronic structure calculations (plane wave DFT if possible), statistical thermodynamics, molecular dynamics. Skills in Python, bash scripting, Fortran 90 and machine-learning would be appreciated. The PIIM
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objective of the project is to understand the underlying soil physical and microbial mechanisms governing changes in soil organic carbon stocks and greenhouse gas emissions under different types
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bench, combining the advantages of real-time software models and real equipment, contributes to the reduction of the number of test runs and safe maintenance. Test benches cover many different areas like
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ultrabroadband mid-infrared intrapulse difference frequency generation sources. You will perform multispecies detection in demanding applications such as environmental and exposure monitoring, and in the green
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field. Solid background in digital IC design and digital signal processing. Hands-on RTL design skills (SystemVerilog / Verilog / VHDL) plus scripting (Python / MATLAB / C/C++). Strong command of English
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Python for scripting and data analysis, metabolite ID via MS/MS and annotation (e.g. SIRIUS, HMDB, authentic libraries etc.), statistical uni- and multivariate analysis, data visualization (PCA score
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a difference: whether you’re exploring the future through research, inspiring students in the classroom, or helping shape everything that makes our education and research possible. PhD in