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aptitude for learning molecular biology and the human genome. Documented knowledge of statistical theory and methods, data mining, and machine learning methods. Documented shell script, R, Python, and C
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. In addition, the following are requirements for the role: Strong programming and quantitative skills, particularly in Python and/or R. Experience in deep learning, machine learning, or large-scale
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the positive ones for different stakeholder groups, as a basis for policy making? Are you interested in spatial optimization algorithms and uncertainty assessment? Then this PhD position at the Department
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with mechanistic differential equation models to understand signalling differences between individual cells. You will develop open-source computational tools (www.github.com/PEtab-dev/petab_sciml) and
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of this master thesis is to evaluate the economic impact of different policy instruments on DAC economics. You will review existing policies for DAC and model the impact of these on the cost of CO2 capture and
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, or density ranges. We recognize that acoustic-based abundance estimation may ultimately require multiple complementary approaches that address different components of the acoustic observation process and
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part of change Development of novel image and video representations Research on alignment between different visual representations, e.g. foundation models Research on properties of learned visual
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Python scripts, calibrate specialised instrumentation and solve technical challenges that directly support researchers conducting experiments in a unique outdoor laboratory. Working alongside researchers
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ingredients, a process that is traditionally slow because each substrate–strain combination behaves differently. By applying machine learning to historical experimental data, we can predict high‑potential
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including transformers, self-supervised learning, foundation models, autoencoders or related architectures; strong programming skills in Python and experience with a deep-learning framework such as PyTorch