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samples, lack of training data and sample variability. In this project we aim to develop AI/ML workflows for improved quantitative analysis of LNPs. Your responsibilities will include optimisation of data
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steps in workflows and implement optimisations to maximise yield and data quality Gain experience in interpreting sequencing data and performing quality control in close collaboration with computational
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power. The work involves quantifying conflicts and synergies between different sustainability goals in the forest landscape using simulation and optimisation. The analysis will be based on spatially
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, simulation, optimisation, or another relevant field or an equivalent foreign degree. This eligibility requirement must be met no later than the time the employment decision is made Strong written and verbal
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(R2) Application Deadline 3 Aug 2026 - 21:59 (UTC) Country Sweden Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU
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conversion, automatic control, energy-storage systems, electrical drives, charging infrastructure, system modelling or optimisation. Experience in modelling, simulation or experimental validation of electrical