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. Daniel Merkle. The overall research project is based on the novel application of formalisms, algorithms, and computational methods from computer science to the design of microbial communities, ultimately
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(CAD, e.g., SolidWorks, CATIA) and engineering (CAE, e.g., Abaqus, Ansys) software tools commonly used in additive manufacturing, structural design and related research (e.g., parametric design tools
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culturing, etc.) Strong interest in phage biology & antimicrobial resistance Preferred: Experience with omics data analysis (esp. RNA-seq, proteomics) Bioinformatics tools and computational skills (R/Python
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engineering, or a closely related field. Knowledge on SSM algorithms, Hands-on experience with layout and tape-out of CMOS chips. Experience in AI chip prototyping and hardware-software co-design. Solid
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, and Computational Social Science. This position is funded under the DTU-JRC Collaborative Doctoral Partnership. Responsibilities and qualifications Your primary responsibilities are: Become familiar
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of AI/ML will be an added advantage. Proficiency with optimization tools and software like GAMS, CPLEX Proficiency with programming languages preferably Python, Matlab Fluency in communication and
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computer science and control systems architecture, advancing all the above disciplines. Building energy flexibility is an important resource for balancing and load shifting in energy networks, especially
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, compression, learning, and inference for classical and quantum data. The stipends are within the general study programme Electrical and Electronic Engineering or Wireless Communications, and available from
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engineering, in an exciting combination of academic and industrial environments. Responsibilities and qualifications Within the scientific area, the researcher is expected to advance the Department's activities
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partners across Europe to deliver a world-class doctoral training programme in risk assessment, resilience engineering, and smart technologies. Its scientific vision targets: (1) the development of a