41 machine-learning-"https:" "https:" "https:" "The Open University" positions at VIB
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
, scale and resolution in which in vivo pathways of immune cells can be unraveled. Furthermore, it provides a goldmine for training causal machine learning models to move towards precision medicine
-
are expanding our mission to harness the power of artificial intelligence for life sciences research, innovation, and impact. We are now looking for an experienced Machine Learning Expert to establish and run a
-
: 10.1101/2025.09.08.674950), and AI/machine learning. We work closely with clinicians to translate our findings into clinical practice, focusing on genomically complex sarcomas and haematological
-
work includes https://doi.org/10.1101/2025.0... and https://doi.org/10.64898/2025.... Profile You have: A PhD in structural biology, cell biology, biophysics, bioengineering, or a related
-
includes https://doi.org/10.1101/2025.0... and https://doi.org/10.64898/2025.... Profile You have: An MSc (or equivalent) in structural biology, cell biology, biophysics, bioengineering
-
analysis Embedding within a computational team, with extensive experience in computational biology and machine learning. Embedding within an experimental team, with direct availability of experimental
-
analysis Background in biomedicine and digital pathology What we offer Embedding within a computational team, with extensive experience in computational biology and machine learning. Embedding within
-
: https://europepmc.org/article/MED/35021063 , https://europepmc.org/article/MED/31819264 , https://europepmc.org/article/MED/31561945 , https://europepmc.org/article/MED/39747019 Profile Master’s in bio
-
with large-scale data analysis, such as genomics or transcriptomics data Experience with a workflow management system such as Snakemake or Nextflow A willingness to learn and apply machine learning
-
of novel mechanistic insights is gained through the application of novel probabilistic deep-learning models that automatically extract biological and statistical knowledge from your in vivo perturbational