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(e.g. Python, R) or a universal programming language (e.g. C#, Java, C++, Rust) Knowledge of the use of relational and non-relational databases Very good English skills (written and spoken) High
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. Strong programming skills in R and/or Python are essential, as well as prior experience in data analysis, statistics, or machine learning. The project involves large-scale single-cell and spatial
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(ESBMC, CBMC, Z3, or similar) – either academic or practical. • Programming proficiency in C/C++, Python, and familiarity with software verification tool development. • Understanding of ML/NLP fundamentals
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highly recommended. Familiarity with experimental techniques for clean-room fabrication and sensitive electrical measurements is highly recommended; a good command over programming languages such as Python
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they will investigate novel Cloud and Edge techniques that are built based on Java, Python and C++. The particular research topics of interest include• application development platforms• programming models
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Universidade Lusófona´s Research Center for Digital Human-Environment Interaction Lab | Portugal | about 24 hours ago
international circulation. International Profile. Be proficient, speaking and writing in English. Technical skills including: experience with Python (Pandas, Numpy, Matplotlib, etc.); experience with popular
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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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systems Experience in the fields of surface catalysis, electrochemistry or thin-film deposition Experience in programming in Python Experience in handling large spectroscopy datasets Experience in assisting
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areas: scientific programming and data analysis (e.g., Python, R, C++, MATLAB), computational modeling, imaging and sensor data processing, bioinformatics, systems biology, or biophysics Familiarity with
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metabolic assays and imaging techniques such as echocardiography or tracer-based studies. Analytical and detail-oriented. You can work with quantitative data and statistical tools (e.g. R, Python, GraphPad