296 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at Nature Careers
Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
prospective postdoc, or in the early stages of postdoctoral training (within 1-2 years of PhD conferral), and have experience in generating and evaluating human or murine immune cells, gene editing, single cell
-
nora.lehotai@umu.se . Visit the NORPOD program page to learn more about the programme. We welcome your application!
-
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
-
cell fate and circuit formation in developing Drosophila brains. The lab combines a variety of cutting-edge experimental and computational techniques including single-cell RNA and ATAC sequencing
-
experimentalists and computational groups. You will be expected to present your results at local and international conferences. Your profile Applicants should hold a PhD in data science, computer
-
interests. www.cemm.at Eligibility Criteria: You must hold a PhD (or will have been awarded your PhD by the time of starting the Pre-ERC Postdoc Program) and your PhD defence date must be no earlier than 2023
-
found on hpc.uni.lu . The activities include classical HPC applications such as simulation and modeling, but also artificial intelligence and machine learning, bridging computational science, with data
-
, probabilistic models Representation learning, self-supervised learning, foundation models Data analysis, non-linear statistics, knowledge management Your profile PhD in Computer Science, Bioinformatics
-
collaboration with our clinical colleagues for investigating visual motion in a group of healthy subjects. The successful applicant holds a PhD degree (or equivalent) in a relevant academic area such as applied
-
currently exploring a range of exciting topics at the intersection between computational neuroscience and probabilistic machine learning, in particular, to derive mechanistic insights from neural data. We