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approaches and will integrate novel hardware (including electrode arrays, microdevices, analytical systems) into automated robotic pipelines You will also apply machine learning-based analyses to imaging and
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Ph.D. or equivalent degree in mathematics, physics, computer science, bioinformatics, or a related field Experience in developing deep learning models Ideally, prior experience in analyzing biological
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analytical sciences. We are looking for talented people to join us. Your responsibilities include: Interdisciplinary research within the project "Complex and Competing Phenomena in Recycled Flame-retardant
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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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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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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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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