Sort by
Refine Your Search
-
to develop and optimize experimental pipelines.Gain experience in both wet-lab and computational techniques to tackle some of the most important questions in microbiome science.Independently drive research
-
decision-making for an optimal energy system, with specific focus on cost-effectiveness, emission reduction, and social acceptability. D2ET will develop a comprehensive digital platform for planning energy
-
together with a Nature-based solution should be evaluated and compared with other tested technologies. One main goal is to optimize existing technologies, combine them into innovative treatment trains
-
this exciting field of biomedical research, EpiSignal offers a state-of-the-art interdisciplinary training program at the intersection of cell signaling and molecular epigenetics, that optimally prepares doctoral
-
principles as well as material properties of extremely thin silica membranes. In this project, you as a PhD candidate will carry out: detailed theoretical studies and optimization of light guidance in HCFs
-
, graph theory, satisfiability problems, discrete optimization. Strong interests in chemistry as well as proven competences in programming and ease with formal thinking are a necessity. This PhD project is
-
therapeutic’s efficacy • Culturing primary human cells and cell lines • Conducting molecular biology assays • Creating and validating viral delivery systems • Optimizing
-
transmission. The successful candidate will work on elucidating the regulation of these channels and developing and optimizing gene therapeutic approaches in mouse disease models to prepare for putative future
-
defects. The charge transport will be implemented stochastically to mimic nature. A significant focus of the project will be to apply machine learning techniques to optimize the model and enable charge
-
contemporary data-driven techniques. Computational methods such as optimization, filtering algorithms, predictors, etc. Software and coding skills with, e.g., Python, MATLAB, R, C++, Julia, potentially HIL