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designing and benchmarking integration algorithms. The position is situated in the Intelligent Data Engineering Lab and will be supervised by Dr. Jan-Christoph Kalo and Prof. Paul Groth. What you will do
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, develop analytic tools for genetic data, and contribute to statistical modelling. In addition to pre-specified work outlined in the Starting Grant, you will have the opportunity to develop related
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, cloning and genetic manipulation (essential) Prior experience with gene editing and/or cell engineering (e.g. CRISPR/Cas or related techniques - essential) Expertise with mammalian cell culture is desirable
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construction, and a robust foundation in statistical spectral analysis, including familiarity with (or strong interest in) chemometrics and/or machine learning algorithms. Job requirements The Ideal Candidate
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biological sciences (essential) Strong background in molecular biology, cloning and genetic manipulation (essential) Prior experience with gene editing and/or cell engineering (e.g. CRISPR/Cas or related
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construction, and a robust foundation in statistical spectral analysis, including familiarity with (or strong interest in) chemometrics and/or machine learning algorithms. Job requirements The Ideal Candidate
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of functional glycans in situ and development of advanced infection model systems to study the role of functional receptors. These models will include (genetically engineered) stem cell-derived 2D and 3D
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that is focused on the detecting of functional glycans in situ and development of advanced infection model systems to study the role of functional receptors. These models will include (genetically
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work to discover cell specific isoforms and relate them to pathological signatures and genetic risk factors in ALS patient tissue. You will apply supervised and unsupervised machine learning methods
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motivation to independently formulate research projects and carry them through to completion; Mathematical skills and command of standard software packages for implementing of optimization algorithms, and a