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research environment focusing on integrating multi-source data and developing novel algorithms to address the challenges posed by global environmental change. You will focus on integrating experiments, field
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experience and enhanced potential to receive an ERC Starting Grant in the future. Open to both PhD (natural sciences) and MD (medical sciences) holders. From a variety of academic backgrounds: molecular
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will have the opportunity to investigate innovative solutions using machine learning algorithms and predictive modelling techniques in the context of a collaborative project with Goodyear Luxembourg (one
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scientists. The Engblom lab works as a team and is dedicated to fostering the next generation of scientists, so we welcome candidates who are interested to teach and mentor budding scientists. Requirements PhD
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algorithms to analyze OMICS data (e.g., genome, transcriptome, proteome, microbiome) from patient samples and basic research perform single-cell RNA-Seq and spatial transcriptomics analysis apply artificial
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mechanism. Recent developments in protein structure prediction and protein de novo design have opened new possibilities for probing such mechanisms. The project will seek to use existing algorithms to new
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twins together with two PhD students, especially to propose new models and algorithms for complex maneuvers, and building a parametric autonomous model of drivers reproducing a close to reality human
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to develop a 3D-generative algorithm for pharmaceutical drug design by using or combining novel machine learning approaches? How would you integrate machine learning, physics-based methods in an early-stage
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implementing inversion algorithms, including a focus on the integration of spatially constrained regularization schemes. Collaborating with forward modeling experts to ensure seamless integration with a recently