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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | about 2 months ago
of particle size, shape and concentration. Your profile We seek a motivated early-career researcher with a PhD in physics, engi-neering, meteorology, or a related field, eager to advance our understanding
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participants, and mathematical / statistical modeling. Requirements for employment are a completed PhD degree in a relevant field (Linguistics, Cognitive Science, Psychology, Philosophy, or similar), near native
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soon hold) a PhD degree in Linguistics or a similar Language Science area are eligible for the role. The ideal candidate for this position has: a solid background in formal linguistics, particularly
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Your Profile Doctorate (PhD) in Ecology, Soil Ecology, or a closely related discipline Expertise in identifying soil invertebrates Experience with the analysis of food webs or trophic interactions
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the achievement of the project’s goals. Assist in preparing reports for the MANTRAMS project. Your Profile: Completed PhD or equivalent in Anthropology, Sound Studies, Religious Studies, Asian Studies, Indology
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#publish findings in international peer-reviewed journals #PhD in Geography, Sustainability Sciences, Ecological or Environmental Economics, System Dynamics, or related fields #proven experience in system
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phenotyping, including image analysis evaluations, for trait quantification Handle NGS datasets for RNAseq or SNP detection and linkage analysis using R Your qualifications and skills: You have a PhD or
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will work with PhD students and a fellow postdoc. You will also become an integral part of the Multiscale Cloud Physics Group currently being established by Dr Franziska Glassmeier at the Max Planck
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advanced data-driven methods and have the autonomy to set your own scientific emphasis. As team member of the ERC Starting Grant “MesoClou”, you will work with PhD students and a fellow postdoc and be
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Your Job: Lead the development and fine-tuning of AI models and LLMs specifically tailored for data mining in the physical sciences and engineering Fine-tuning and evaluation of open-source LLMs