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learning pipeline in Python (using e.g. PyTorch) - validation of your results in collaboration with colleagues from various application areas (cross-disciplinary) - publication and presentation of your
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the analysis and simulation of analog, digital, or mixed-signal circuits, including SPICE and related tools (LTspice, Cadence, MATLAB, Python) Excellent communication skills and ability to work in a team are
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lead to a PhD position at SPMS in NTU Singapore (based on performance). Key Responsibilities: Contribute to the development of algorithms Develop codebase in Python and perform large-scale simulations
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Leibniz-Institute for Food Systems Biology at the Technical University of Munich | Freising, Bayern | Germany | 5 days ago
programming, preferably Python and R, is required. Experience with mass spectrometry data, in particular metabolomics, and geometric machine learning is a plus. In addition to above-average interest in
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software as python packages Report findings and methods in conference and journal papers Your profile Masters, Diploma or equivalent degree in IT/computer science/statistics/applied mathematics/data science
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in R and/or Python Excellent communication skills and fluency in English (oral and written) Independent, proactive, rigorous, results-driven, solution-oriented, and a critical thinker Collaborative
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with emerging memory devices Experience with simulation tools (LTspice, Cadence, MATLAB, Python) Interest in brain-inspired computation, energy-efficient hardware, and experimental validation Ability
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pipeline in Python (using e.g. PyTorch) validation of your results in collaboration with colleagues from various application areas (cross-disciplinary) publication and presentation of your scientific results
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, Computational Biophysics, or a closely related field Strong programming skills (e.g., Python, C/C++) Knowledge of machine learning frameworks (e.g., PyTorch, TensorFlow) Very good English language skills, ability
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communication skills in English.-A collaborative and curious mindset.-Experience with biological or solid-state nanopores, DNA nanotechnology, single-molecule microscopy, or programming/data analysis (e.g., Python