16 modelling-and-simulation-of-combustion-postdoc Postdoctoral positions at UNIVERSITY OF HELSINKI
Sort by
Refine Your Search
-
with the land surface model to conduct regional simulations; Flux and concentration footprint modelling; Post-processing of eddy covariance data, gap filling and data analysis; Plan, coordinate and
-
investigation and will develop an advanced computer modeling framework. By simulating processes at various scales, from the atomistic to continuum, we aim to reveal how temperature and saturation fluctuations
-
agent-based modeling or another relevant computational approach for the simulation of managed retreat. We look for a candidate in sustainability or environmental social sciences or a related field who
-
metagenomics assembly” funded by the Research Council of Finland in the research group of University Lecturer Leena Salmela. We develop models, algorithms and data structures for high throughput sequencing data
-
sequencing data from up to 10,000 trees. We are using birches (Betula) as our model organism, as they have a relatively small genome, they are adapted to their local environments and there are accelerated
-
full-time, three-year fixed-term contract starting in September 2025 (or later by agreement). The position includes a six-month trial period. Postdoc applicants must hold a doctoral degree by the start
-
project CONFSTAT – Conformally invariant and near critical models in statistical field theory. The work of the postdoctoral researcher will focus on studying conformally invariant models of statistical
-
(FIMM) , University of Helsinki, is currently seeking a highly-motivated postdoctoral researcher to join our interdisciplinary team. Project overview This project aims to develop machine learning models
-
using unique novel mouse models, spatial technologies and analytical methods. Postdoctoral Researcher in Functional Cancer Microbiome through the NORPOD program NORPOD is a collaborative postdoctoral
-
Cancer Medicine at the Faculty of Medicine, University of Helsinki. The project will focus on developing approaches for gene regulatory network modeling on deconvoluted bulk data, with applications to pan