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should hold a PhD degree in molecular biology, biochemistry, cancer biology or related fields. Expertise in biochemistry, transcriptomics, NGS data analysis and basic programming in R/Python is a pre
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author) in the field of computational biophysics (molecular dynamics simulations and/or quantum chemistry). Any experience in development and application of AI/ML methods in tandem with modeling and
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researcher will be mainly supervised by Prof. Aki Manninen with an aim to develop cellular models and molecular strategies to validate and establish novel biosensor technologies. The position is part of a
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significant merit: (mammalian) cell culturing techniques, in vivo models, high throughput screening, molecular biology or bioinformatics excellent written and verbal communication skills (in English) strong
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biology studies to identify and characterize adaptive homeostatic responses in novel disease models. These insights hold significant translational potential, particularly for pharmaceutical companies
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will apply and develop machine learning and Bayesian methods adapted to longitudinal design In the Research Council of Finland Project 'Body weight trajectories; Molecular entropy and aging with multi
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leveraging existing databases of abundance time series and genetic sequence data and using a combination of modelling approaches and synthesis to systematically quantify change across multiple biodiversity
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biology studies to identify and characterize adaptive homeostatic responses in novel disease models. These insights hold significant translational potential, particularly for pharmaceutical companies
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bioassay development and validation previous experience on one or more of the following fields is considered a significant merit: (mammalian) cell culturing techniques, in vivo models, high throughput
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potential candidate will perform large-scale machine-learned driven molecular-dynamics simulations of ion irradiation in phase-change materials, to obtain realistic models and evaluate the resilience