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                ) in the field of spatial equilibrium modeling, starting on 01.11.2025. PhD positions are funded for 3 years with a 75% share of the total E13 salary in accordance with the German public tariff scheme 
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                . The department of Atmospheric Chemistry (ACD) and Atmospheric Microphysics (AMP) research the chemical and physical properties of aerosol particles and their interactions with clouds. Process-based laboratory 
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                such as the NEPS. Potential research areas include (but are not limited to): Item response modeling of achievement tests Analysis of process data (e.g., response times) to enhance competence measurements 
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                phenomena such as the spread of misinformation or the formation of filter bubbles. For this, we rely on rigorous probabilistic methods to model and analyse the intrinsic complexities of these systems 
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                University Sports Center, further training opportunities and language courses, Company restaurant with a variety of breakfast and lunch dishes. The employment contract, including remuneration, is based 
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                The position is to be filled within the Marie Skłodowska-Curie Doctoral network METAMIC 3 - Metaproteome-based leveraged microbiome management in the context of One Health. METAMIC 3 is funded by the European 
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                innovative machine learning architectures for the mining, prediction, and design of enzymes. Combine state-of-the-art ML (e.g., deep learning, generative models) with computational biochemistry tools 
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                plant genetic mechanisms that coordinate mycorrhizal interactions with plant P and water status, root system development, and soil microbial communities. Using maize and rice as models, we will: Determine 
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                level of E13 with 75% working time. An annual basic salary plus and annual bonuses based on TVöD Bund are possible. About PDI The Paul-Drude-Institut is part of the Forschungsverbund Berlin e.V. and a 
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                data. You bring first experience with biostatistics methods, e.g. with mixed-models. You are familiar with data analysis using programming languages like R, and/or Python. You have excellent