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fabricate demonstrators in our state-of-the-art Nanofabrication facility and perform experiments in the terahertz characterisation facility (Kollberg Laboratory ). As a PhD student, you are expected
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Documentation and description of other relevant experiences or competences. The application must be written in English or Swedish. Attached documents must be in pdf format. Applications must be submitted
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quantitative interdisciplinary program. Excellent written and oral communication skills in English are required. Demonstrated capacity to integrate forestry and economics concepts, experience writing scientific
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in a large project rather than on your own in a single project. The following experience will strengthen your application: Experience in energy storage, organic synthesis, or materials characterization
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include: Developing the model using open-source Python software Planning and conducting experiments Analysing teardown reports and experimental data Validating and improving the model Publishing results in
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CST Microwave Studio, HFSS or EM Pro for antenna modeling and design is required, as is experience with programming languages like MATLAB, Python, or similar for antenna array analysis and algorithm
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to collaborate with others essential. You should also enjoy sharing your work and results with both internal and external stakeholders. Previous experience with energy or environmental systems analysis, LCC (life
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, microbiology or mycology. Familiarity with mycology and the Nordic forest ecosystems is desired. Previous experience with ecology, molecular biology work, bioinformatic and nature conservation are meritorious
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, biomechanics and computational approaches. A relevant background is a degree in plant biology and/or related fields. Other requirements are: Solid background in cell and molecular biology. Experience in standard
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Stockholm University. Requirements: An MSc, including a thesis of at least 30 hp in Biotechnology, Bioinformatics, or related fields. English as a working language, with Swedish as a strong merit. Experience