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to work on topics at the intersection of applied probability and analysis. The group around Pierre Nyquist currently consists of three PhD students and is focused on questions in probability theory and
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. Contract terms The employment is limited to seven months at 20% rate, or the equivalent. Mandatory qualifications: A Bachelor's degree in chemistry, chemical engineering, physics, materials science or
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Machine Learning Integration Develop and implement machine learning algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC
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, you should have: A Master of Science degree in Mechanical Engineering, Mathematics, Physics, or in relevant fields of fluid/structure dynamics and acoustics. Very good knowledge of English, both spoken
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algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC) to accelerate design iterations Integrate ML approaches with finite
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a genuine interest in research and collaboration. Mandatory: To succeed in this role, you should have: A Master of Science degree in Mechanical Engineering, Mathematics, Physics, or in relevant fields
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the Department of Life Sciences collaborating to combine knowledge in biology, chemistry, and physics to study nucleic acids, proteins, and lipids and their interactions with cells. Within the Holme group, we
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characterization (SEM, EDX, etc) Aerosol physics Data analysis and programming (e.g., MATLAB, Python, or R) Interdisciplinary teamwork Fieldwork and particle sampling e.g. on/from vehicles Swedish language skills
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should be labeled with your name and documents saved as PDF files as follows: CV Other (optional: certificates, diplomas, etc.) In this application process you will asked to answer a few questions
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should be labeled with your name and documents saved as PDF files as follows: CV Other (optional: certificates, diplomas, etc.) In this application process you will be asked to answer a few questions