51 algorithm-development-"St"-"St" PhD positions at University of Groningen in Netherlands
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% of their time to teaching in years 2-4. FEB encourages early stage researchers to develop a healthy work-life balance, for example by facilitating those wishing to combine family planning with excellent
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contribute 20% of their time to teaching in years 2-4. FEB encourages early stage researchers to develop a healthy work-life balance, for example by facilitating those wishing to combine family planning with
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and foster equitable decision-making? To answer this question, the research will explore areas such as the following: Characterizing human-AI collaboration for bias mitigation – Developing a conceptual
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collections interact with power, knowledge, and ongoing processes of heritagization. The candidate is encouraged to develop new methodologies that center community-led, ethical, and innovative approaches
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aims at developing tools using large language models (LLMs) for the correction of misinformation about climate change in social media. The successful candidate will develop innovative tools leveraging
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) developing and validating preprocessing pipelines; (3) architecting and comparing spectral-only and multimodal (HSI + NIR + Raman + RGB) deep-learning models; (4) implementing robust sensor-fusion strategies
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are not able to infect anymore. By specifically looking at where and how such antivirals can change viral structure, this knowledge can be used for the development of better, more efficient antivirals that
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: Optimize network design: Develop a robust, scalable thermodynamic–hydraulic framework to size and configure prosumer-based heating and cooling networks under conditions of price volatility, CO2 taxation
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at where and how such antivirals can change viral structure, this knowledge can be used for the development of better, more efficient antivirals that disturb the structure and dynamics of viruses faster and
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such as the following: - Characterizing human-AI collaboration for bias mitigation – Developing a conceptual framework of responsible human-AI collaboration to better understand the role of human oversight