4 machine-learning-phd positions at UNIVERSITY OF HELSINKI

Doctoral Researcher, Adapting Computational Methods To Challenges In Historical Research At Scale

, this project will focus on ensuring that the computational approaches measure what they’re supposed to measure. This includes fine-tuning machine-learning methods to capture different types of change, as

Doctoral Researcher, Political vocabulary of eighteenth-century Britain

of Helsinki (Finland) PhD:  PhD in Digital Humanities or Intellectual History Main supervisor: prof. Mikko Tolonen (University of Helsinki, Faculty of Arts, Digital Humanities) Second supervisor: prof. Eetu

Postdoctoral Fellowship In Single-Cell Spatial Multi-Omics

the findings to clinical data using machine learning. The postdoctoral fellow will perform studies on the metabolism of healthy intestinal cells and tumour initiating cells using state-of-the-art mouse models

Doctoral Researcher, Computational Biophysics

mitochondrial function and dysfunction. An ensemble of multi-scale computational approaches (molecular dynamics simulations, quantum chemistry, machine learning, etc) are applied to study the mechanistic aspects