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(meta-)genomes Experience in the computer-assisted analysis of large biological datasets (e.g., using R, Python, and Bash/Linux environments) Very good written and spoken English skills Ability to work
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experimental data. • Proficiency in scientific programming and data analysis tools (e.g., Python, R, Linux/Unix environments). • Demonstrated track record of publishing scientific results in peer-reviewed
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, fluid mechanics, simulation, and programming (Fortran, C/C++, Python, …). Proficiency in English is a requirement. The position adheres to the European policy of balanced ethnicity, age and gender
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related field with a strong quantitative focus. Strong programming skills in Python and demonstrated experience with machine deep learning frameworks (for instance, PyTorch or TensorFlow), preferably
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multidisciplinary team Basic knowledge of detector systems for particle physics Basic programming skills, e.g., python, Matlab or similar languages Fluent spoken and written English Proficiency of the German language
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of numerical methods Basic programming skills, e.g., Python, Mathematica or similar languages Fluent spoken and written English Proficiency of the German language is a plus. We offer: a unique opportunity to
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(R, Python, MATLAB, or similar). Willingness to conduct fieldwork in Arctic conditions. Proficient in both written and oral English. You will be offered the opportunity to participate in digital
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | about 1 month ago
: Good programming skills, preferably in Python, and strong analytical abilities. A solid background in machine learning, computer security, privacy, distributed systems, or a closely related area
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development Sensor systems and sensor characterization Embedded systems, microcontrollers or FPGA Laboratory work and experimental measurements Signal processing Python or similar programming languages
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experience in Python and, more specifically, in common deep learning frameworks such as PyTorch and jax, for model training and inference have experience with embedded platforms such as FPGAs or RISC-V