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proficiency in Python, R, or MATLAB. Experience with Deep Learning frameworks (PyTorch, TensorFlow) and LLM APIs is an asset. Communication: Fluent English skills, both written and spoken, with a demonstrated
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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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- Significant experience in programming, e.g., in C++, Python or Matlab. Experience with quantum simulators, such as NetSquid, is a plus; - Familiarity with the basic concepts of quantum information and
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knowledge and skills in machine learning - Significant experience in programming, e.g., in C++, Python or Matlab. Experience with quantum simulators, such as NetSquid, is a plus; - Familiarity with the
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. R, MatLab, Python) are expected as is experience in planning and executing fieldwork. Preferable you have experience with various telemetry methodologies to study fish behavior (e.g. PIT, radio
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fields and high-impact journals. The candidate should be proficient and experienced in studying ecology of fish in the wild. Analytical skills and experience with statistical software (e.g. R, MatLab
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delivering presentations. In addition, it would be advantageous for applicants to demonstrate proficiency in at least one scientific programming environment such as Python, MATLAB, or R. Familiarity with
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correction and/or mitigation. Knowledge about networking protocols and distributed algorithms. Experience in programming, e.g., in C++, Python or Matlab. Experience with quantum simulators, such as NetSquid
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highly advantageous: Scientific programming in Python or MATLAB Probabilistic methods, Bayesian inference, or stochastic modelling Structural mechanics, material modelling, or multi-physics simulation Data
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: Scientific programming in Python or MATLAB Structural mechanics, reliability analysis, or probabilistic modelling Data analytics, SHM/SCADA data interpretation, or digital-twin technologies Wind energy systems