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of this Norwegian Cancer Society project. Both standard and advanced methods in molecular biology and cell biology are needed to carry out this project. Thus, the researcher is expected to act as self-driven
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or cryogenic electron microscopy (cryo-EM) Determination of protein ligand binding using biophysical methods (SPR, ITC, or related methods) Experience in the following areas is an advantage: Structure-based drug
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component corresponding to 30 ECTS, which corresponds to one semester. The remaining six months will be allocated to this formal training. Qualifications and personal qualities: The applicant must hold a
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for basic research. The successful applicant will contribute to the further development of the Coincidence Analysis (CNA) method for causal data analysis. Currently, CNA has four key limitations: (I
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. The candidate will work with state-of-the-art analytical instrumentation, generate extensive experimental data sets and analyze them using advanced bioinformatics methods. The work tasks include to: Generate and
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comprises a training component corresponding to 30 ECTS, which correspondsto one semester. Qualifications and personal qualities: The applicant must hold a Norwegian master’s degree or an equivalent foreign
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will be allocated to formal training. As a PhD candidate, you must participate in the Faculty of Humanities’ educational programme . The PhD programme comprises a training component corresponding to 30
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). Potential other methods include laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS), Raman spectroscopy, time of flight secondary ion mass spectrometry (ToF-SIMS), electron microscopy (EM
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microbial genomics, atomic force microscopy combined with vertical scanning interferometry (ATM-VSI), x-ray diffraction (XRD). Potential other methods include laser ablation inductively coupled plasma mass
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will be adapted to the candidate’s background and the evolving needs of the center. Possible directions include the application of rock physics models, Bayesian inversion methods, and machine learning