67 post-doc-in-machine-learning Postdoctoral positions at Technical University of Denmark in Denmark
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tolerant microstructures that can cope well during subsequent in-service use You will work in close collaboration with a group of senior scientists and technicians as well as Post Docs and PhDs. Also, the
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Electrophysiological signal processing of, e.g., EEG, ECG, EMG, etc. Health data science, incl. modern machine, and deep learning methods, Cloud-based platforms like MS Azure or Google Colab Health data standards, like
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, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks
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. We are looking for a candidate with a strong background within food science and fermentation background. A candidate with some experience from industry will be preferred. The Post Doc candidate may
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, including GKP state generation and nonlinear gates. EPIQUE (Horizon Europe): Cluster state generation on photonic integrated chips and its integration into a measurement-based Gaussian Boson Sampling machine
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analysis Close collaboration with an interdisciplinary team. Research and teaching efforts at a section and departmental level as appropriate and relevant (e.g., teach and supervise MSc and PhD student
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materials discovery, materials processing, and structural analyses. We also focus on educating engineering students at all levels, ranging from BSc, MSc, PhD to lifelong learning students. We have about 300
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information about this position may be obtained from Prof Solange I. Mussatto, e-mail: smussatto@dtu.dk . Please do not send applications to this e-mail address, instead apply online as described below. You can
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the above-mentioned research areas (e.g. scp-MS, cell heterogeneity, computational proteomics, etc.) Foster national and international collaborations, both outside and within the university Teach in
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folding of such proteins. Carry out expression and purification for functional characterization of selected proteins. Teach and supervise BSc and MSc student projects Potentially Co-supervise PhD students