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-party research funding are expected. We are particularly interested in a candidate in any field of economics who leverages state-of-the-art machine learning and causal inference methods to innovative
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resides in is to build up technology for data-driven pattern recognition to infer data-driven generalized auditory profiles. The central challenge for this endeavor are the small sample sizes (of typically
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influenced corrosion (MIC) in marine environments. It uses AI-supported models, Bayesian data fusion, and real-time sensor data integration. Your responsibilities include: Development of a digital twin (DT
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, paleobiology, geoecology, evolutionary research, or a related field Experience in computational modeling, analysis of ecological or evolutionary data, or causal inference Proficiency in model calibration
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and optimize large-scale training and inference runs for foundation models on JUPITER (multi-GPU/node, mixed precision, parallelization, I/O optimization) Integrate multimodal data sources (e.g., scRNA
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for inferring signatures of natural selection. The position is supposed to be filled at the earliest possible date and initially funded for 2 years with the possibility for extension. Compensation with all public
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bioinformatic tools, including phylogenetics and methods for inferring signatures of natural selection. The position is supposed to be filled at the earliest possible date and initially funded for 2 years with
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Max Planck Institute for Astronomy, Heidelberg | Heidelberg, Baden W rttemberg | Germany | about 2 months ago
-Neptunes and gas giants (3 years). Developing next-generation techniques for atmospheric characterization through retrievals with machine learning, including techniques such as simulation-based inference
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individual rates of ageing. Role You will extend BrainAGE from global estimates to regional normative models using Bayesian regression and GAMLSS to derive age- and region-specific reference distributions
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Max Planck Institute for Gravitational Physics, Potsdam-Golm | Potsdam, Brandenburg | Germany | 29 days ago
gravitational-wave detectors on the ground (LIGO, Virgo, KAGRA, Cosmic Explorer, Einstein Telescope) and in space (LISA), techniques for the acceleration of gravitational-wave inference, including machine