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Field
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contribute to research on applied machine learning methods that support robust decision-making under uncertainty. This may involve working with structured datasets, panel data, text data, regulatory documents
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advancing both technology and manufacturing readiness levels. These PIC-based solutions are expected to support the transition from complex optical laboratory setups towards more scalable and deployable
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of many more complex processes that should harbor a wealth of undiscovered druggable targets. Thus, a large space of potential druggable biology is entirely ignored. We aim to fundamentally revolutionize
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arising from finite fields, projective and polar spaces, and related structures. Apply computational methods (e.g. Magma, GAP, SageMath, Python) to test conjectures and explore new mathematical directions
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learning and deep learning techniques to the biological sciences. The ideal candidate will have expertise in artificial intelligence, with a specific focus on deep learning applications in structural biology
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biochemical to molecular biology and bioinformatics approaches. Collaborations with structural biologists are possible. Your profile Applicants should hold a PhD in Molecular Biology, Biochemistry, Cell Biology
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Research Center for Molecular Medicine (CeMM), ÖAW | Vienna, Virginia | United States | about 2 months ago
functional approaches to map how leukemia-driving oncoproteins act in the context of phase-separated biomolecular condensates and how these structures regulate epigenetic states and cancer-associated gene
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methods for assessing whether, how, and to what extent these transition pathways are driving structural change. You will: select and co-develop indicators and methods to assessing circular transition
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instrumentation for analyses of volatile compounds, molecular analyses of microbial community structure and activity, as well as incubation and climate chamber facilities. Marine Biological Section, located in
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-protein complexes using structural proteomics approaches (cross-linking MS, HDX-MS), AlphaFold-based structural prediction, cryo-EM (through collaborations), and targeted mutagenesis with biochemical