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), statistical analysis of LHC data or beyond-the-Standard-Model phenomenology, is meriting. Experience with large-scale training on GPU and HPC systems, with design of experiments and active learning, with open
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-performance computing, particularly in the theory of efficient string and data structures, sequence indexing, and large-scale data analysis. Experience with the Burrows–Wheeler transform, pattern matching, and
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Requirements A doctoral degree or an equivalent foreign degree. This eligibility requirement must be met no later than the time the employment decision is made. Expertise of large scale data handling Experience
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: (Only in Swedish). Additional qualifications It is advantageous to have documented knowledge and experience in one or more of the following areas: CAD design and microfabrication in a clean-room facility
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experience and track record in using open databases and bioinformatic tools and services. Strong programming skills for developing computational tools or data workflows (Python or similar), with good software
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a demonstrated interest in cell biology and biological modelling. Have experience interpreting biological datasets, particularly imaging data and multimodal datasets combining imaging and molecular
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drivers of regulatory innovation in conifers (Norway spruce and Scots pine). The scholarship is full-time for two years with starting date August 1, 2026, or according to agreement. Departmental specific
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backgrounds and with complementary strengths. Great emphasis will be placed on personal skills. Join us at KTH KTH shapes the future through education, research and innovation. As a leading international
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. Documented research experience in modern deep learning (e.g. generative models, Bayesian deep learning or large pre-trained models) and excellent programming skills in Python and a modern deep learning
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. Required qualifications: PhD in a field such as physics, systems biology, applied mathematics, machine learning, or related fields. Strong programming skills (e.g. Python) and experience with modern ML