Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
Master/engineer degree in computer science, applied mathematics, data science with background in image processing, imaging inverse problems, deep learning and optimisation. Good coding skills for numerical
-
fields for several applications in the field of computer vision and inverse problem [SLX+21]. As far as the modeling of data term between distributions is concerned, one idea would be also to follow
-
, but are not limited to, neural coding in the visual cortex, multimodal information processing, state-dependent processing, visual perception, development of imaging tools for in vivo neuronal recordings
-
opportunity for an outstanding scientist to establish an independent research program at the interface of biology and computer sciences, in one of the five major DYNABIO-affiliated institutes (C3M, iBV, IPMC
-
various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
-
The candidate should preferably have a PhD in Computer Science or Robotics with a solid background on deep learning and 3D scene understanding. Experience with LiDAR and Computer Vision is a plus. The candidate
-
Discrete geometric representations such as meshes are a crucial part of engineering simulation pipelines. The success and fidelity of numerical methods heavily depend on the accurate representation
-
genetics, genomics, imaging processes, computational biology and biochemistry. Our goal is the deep and detailed understanding of fundamental mechanisms in plant biology that may then also be used to develop
-
. Required Skills and Candidate Profile The project is intended for a candidate with: ➢ Skills in medical image processing and deep learning adapted to clinical applications. ➢ A good knowledge of Python
-
observed in Drosophila larvae. This interdisciplinary project combines biology, neuroscience, and computational modelling to understand how the larva’s body’s physical properties influence its motor control