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Field
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Proven laboratory experience and programming proficiency (Python or a comparable language) Ability to work independently and self-reliantly, while maintaining strong teamwork and collaboration skills
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the analysis of seismological data Programming in Python Project 2: (preferred) Knowledge of machine learning, or experience in processing large datasets or experience with the analysis of local seismicity
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: It is advantageous to have experience in one or more of the following areas: -Machine Learning & Bayesian optimization (Python, Supervised learning, Multi-objective optimization) -Additive
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- Practical experience in working with RNA (RNA extraction, RT-PCR, RNA sequencing) - Knowledge in programming languages like R or Python for data manipulation and analysis - Experience in quantifying plant
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good knowledge of experimental research methods and statistics, experience with sta-tistical software (e.g. JASP, R)•Programming skills (e.g. in Matlab, Python/Psychopy and/or R) or willingness
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fields (genetics, genomics, bioengineering, applied mathematics) Obtained or will obtain a Master’s degree in the above fields (For biologists) Intermediate programming skills in R or Python and prior
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code via differential testing)We focus on techniques that apply to real-world software systems. E.g., in the past, we have developed techniques that find and fix bugs in widely used Python, Java, C/C
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scientific questions Proficient in scientific software (e.g., Gatan DigitalMicrograph, Python, Origin, Matlab, SRIM/TRIM) Basic knowledge of scientific data analysis and statistical evaluation Good command
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data analysis (e.g., Python, R, C++, MATLAB), computational modeling, imaging and sensor data processing, bioinformatics, systems biology, or biophysics. Familiarity with simulation environments
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2D NMR spectroscopy (1H, 13C, hetero-nuclei), single crystal X-ray diffraction analysis, IR spectroscopy and mass spectrometry are essential. Experience with programming/data visualisation using Python