Sort by
Refine Your Search
-
Listed
-
Country
-
Field
-
outstanding candidates whose work lies at the intersection of statistics, machine learning, data analytics and modern AI algorithms. This includes, in particular, statistics for high-dimensional and complex
-
of the candidate), in visualization and data analysis, cooperative systems, data mining and machine learning, education, didactics and entertainment computing, or Neuroinformatics. Across faculties, renowned
-
team, your expertise in AI and other cognitive computing methodologies, such as but not limited to machine learning (ML), large language models (LLMs), small language models (SLMs), natural
-
this, the Center will develop and deliver research-based education for the future workforce – spanning bachelor, master, PhD, and life-long learning. The Center is based upon grant funding of DKK 123 million from
-
NOVA Institute for Medical Systems Biology (NIMSB) announces Four Independent Group Leader positions
for integration of large-scale omics datasets, and application of machine learning and statistical modelling for decipher cell and tissue behaviour, elucidate disease mechanisms, and enable patient stratification
-
: 30057201; Nature Genetics, in press) and has pioneered novel machine learning approaches for analyzing genomic data (e.g., bioRxiv 517565). The Kübler Lab is integrated into the extensive Berlin research
-
an excellent scientific track record. Proven expertise in environmental genomics, metagenomics, or large-scale omics data analysis. Experience with machine learning or AI approaches in biological data is an
-
to candidates from a broad range of AI subfields, including, but not limited to machine learning, generative AI, computer vision, representation and reasoning, natural language processing
-
computational modeling and/or analysis of complex biological systems, integrating state of the art tools such as machine and deep learning approaches. Experience in managing biological databases and statistical
-
geological field-based methods and big data applications and machine learning methods. Research focus will be on feedback processes between erosion, sedimentation, tectonics and climate, and topics could