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for predictivemodelling and large foundation models for earth systems. Skillsetssuch as programming in Python/R, Google Earth Engine, JavaScript, database management environments, Geographical AI, and machine learning
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record in peer-reviewed international journals Experience with remote sensing, LiDAR, and GIS applications Programming skills in Python Background in LiDAR point-cloud analysis and vegetation structure
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Experience with scientific programming (e.g. in python) Experience with modelling of disordered materials is seen as an advantage Experience with automated computational workflows is seen as an advantage
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in carrying out the planned research. Below is listed experience and skills that will be considered: Proficiency in statistical and programming languages such as Perl, Python, and/or R. Experience
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methods, omics data analysis, and spatial tools is highly valued. Programming expertise in Python and/or R is essential. As a person you demonstrate high ambitions. You are equally innovative – and result
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Python or similar. Experience with optics and/or reflectometry for X-rays and/or neutrons. Personal drive and self-motivated. Good communication skills in English, both written and spoken. Being able
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field that provides a sufficient degree of background in computer science, artificial intelligence, mathematics and data science. Fluency in English, Python, and C/C plus plus are required. Experience
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) Experience with automation and scripting (Bash or Python) Experience managing virtualization platforms (e.g. OpenStack or Proxmox) Basic knowledge of network security (firewalls, VLANs, VPN) Knowledge
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., in C++, Python or Matlab. Who we are The successful candidate will be hosted by the Section on AI & Sound. This section is led by Prof. Jan Østergaard. A dedicated supervisory team composed of experts
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methods, omics data analysis, and spatial tools is highly valued. Programming expertise in Python and/or R is essential. As a person you demonstrate high ambitions. You are equally innovative – and result