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modeling of magnetic materials using first-principles methods. Good knowledge of programming is required. Meritorious experience for the position is demonstrated knowledge of Git, Python, Bash and VASP. Good
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Python, Matlab, and R, and good UNIX knowledge are essential skills, as well as familiarity with biological omics data analysis techniques. Admission Regulations for Doctoral Studies at Stockholm
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. Good skills in programming (e.g. Matlab, Python, C/C++) Strong written and verbal communication skills in English The following experience will strengthen your application: Experience with radars
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purification and/or Python code development. Consideration will also be given to collaborative skills, drive and independence, and how the applicant, through experience and skills, is deemed to have the
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to the application deadline. PhD in computer science, electrical engineering, biomedical engineering, or a related field. Experience in Python programming, natural language processing, and multimodal deep learning
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structural biology. Merits are: Experience from protein production and purification and/or Python code development. Consideration will also be given to collaborative skills, drive and independence, and how
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transient absorption spectroscopy. Proficiency in ultrafast laser pulse compression, including pulse characterisation techniques like FROG and autocorrelation. Good coding skills (e.g. Python, MATLAB, LabView
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learning, deep learning and relevant software framework (R and Python) is highly desired. Very good oral and written communication skills in English are required. Emphasis will also be given on personal
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language such as Python, R, C, or MATLAB Fluent in English for communication and scientific writing Merits: Knowledge and experience in: Data Science and Statistics Radio Frequency Digital Signal Processing
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the documentation requirement for doctoral education . Skills and personal qualities Necessary Skills: Strong programming skills in languages such as Python. The ability to work both independently and collaboratively