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Fritz Haber Institute of the Max Planck Society, Berlin | Berlin, Berlin | Germany | about 8 hours ago
or Postdoctoral position (m/f/d) - Interpretable Machine Learning for Catalytic Reaction Network Discovery. A full-time PhD or Postdoctoral position is available in a collaborative Max Planck research
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students and technicians Maintain accurate documentation of protocols and instrument logs; liaise with service and facility management Your profile: PhD (or equivalent) in analytical/biological chemistry
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-scale controllable, and cost-efficient disease models by bringing together experts in physical chemistry, physics, bioengineering, molecular systems engineering, machine learning, biomedicine, and disease
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timings) affect the metabolome and proteome of rapeseed seeds. Your findings will serve as molecular fingerprints to support Deep Learning models for hybrid development. Whom we are looking for: An early
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Basic knowledge of analytical chemistry, especially in trace element analysis Experience with inductively coupled plasma mass spectrometry (ICP-MS) Experience with laser ablation ICP-MS is an advantage
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science, meteorology, or a related discipline Strong experimental skills; strong experience in analytical chemistry, mass spectrometry, and trace gas measurements using CIMS techniques Enthusiasm
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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and
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-level of spoken and written English, and robust conceptual and analytical skills, as documented through prior research publications. Strong candidates will also have familiarity and experience with
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following position Postdoctoral researcher (m/f/d) in Environmental Data Science and Machine Learning for the project BoTiKI Location: Görlitz Employment scope: full-time (40 weekly working hours) / part
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of these patients. The goal of this project is to combine cutting-edge multi-omics technology, data analytics, machine learning and clinical samples from the human eye to decipher new insights into disease mechanisms