233 algorithm-development-"Multiple"-"Simons-Foundation"-"Prof" "UNIS" Postdoctoral positions at Nature Careers
Sort by
Refine Your Search
-
Listed
-
Country
-
Field
-
· Gender-friendly environment with multiple actions to attract, develop and retain women in science · 32 days’ paid annual leave, 11 public holidays, 13-month salary, statutory health insurance
-
and analysis of mathematical methods for novel imaging techniques and foundations of machine learning. Within the project COMFORT (funded by BMFTR) we aim to develop new algorithms for the training
-
opportunity to contribute to cutting-edge research at the intersection of artificial intelligence, machine learning, and healthcare. The successful candidate will develop and apply advanced machine learning
-
to a solid research program with clear project goals and strong support for career development. Key Research Techniques & Models: Mouse models: Knockout, conditional knockout, transgenic, and patient
-
metabolism. The candidate will be involved in the field of basic and translational diabetes and obesity research and drug discovery. The research in the lab involves the development and implementation
-
Nanomaterials that detect protein-structural changes Nano-optical devices for protein-signal sensing AI algorithms for protein structure and dynamics prediction Outstanding Postdoctoral Training Strategy
-
interdisciplinary teams to apply developed algorithms to real-world datasets and generate valuable biological insights. Perform integrative analyses of multidimensional datasets within the context of basic immunology
-
sequencing and synthesis to design useful cell behaviors. The scope of this project is to combine multi-gene control technology and computer algorithms to develop a foundational discovery platform for future
-
As a fellow you will join our faculty in the Department of Biostatistics, providing statistical support and developing innovative biostatistical methods for research projects at the cutting edge
-
Postdoctoral Research Associate - Human Organoid/Assembloid Models of Schizophrenia-associated Risks
related fields within the last 3 years and who have experience in organoid development, patch-clamp techniques, 2-photon imaging, and computational neuroscience. The successful candidate will lead an