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analysis. Hands-on experience in building/assembling lab/pilot-scale equipment. Knowledge of modelling and programing skills in Python C/C++, MATLAB and/or LabView. Basic knowledge in electronics. 3D CAD
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of Python language Knowledge in XRD and/or XRF analysis. Eligibility Appointment to the position of postdoc requires that the applicant has a PhD, or an international degree deemed equivalent to a PhD, within
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of or experience with programming languages and modelling tools such as Python, Fortran, ANSYS, StarCCM+, and OpenFOAM Collaboration and Communication Interest in collaboration with the wider community and the
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publication record in reputable peer-reviewed journals is highly desirable. Proficiency in programming, particularly in R, Python, or other relevant languages, is required. Qualified candidates should also meet
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engineering, computer science, physics engineering, or equivalent) Programming skills in Python or another language Strong work ethic Fluency in English, with the ability to write, communicate, and interact in
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, Python and IDA ICE. In an overall assessment of suitability, emphasis is also placed on personal abilities. All employees at MDU are expected to cooperate and treat colleagues and students with respect
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programming languages (e.g., Python, R). Experience working in a LINUX/UNIX environment. An excellent molecular biology skillset. Experience with NGS library preparation supported by a strong publication record
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and expertise will strengthen an application: proven experience with Unix command-line interface (CLI) and Bash scripting proficiency in a higher-order programming language like Python or R experience
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analysis Deep understanding of community ecology concepts and theories Experience of ecological modelling Competence in data analyses in R and Python Supervision of undergraduate students Teaching activities
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bioinformatics, physics, statistics, computer science, computational biology, or related fields. Experience programming in Python (or R) as well as bash/shell scripting. Experience with machine-learning and deep