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computational approaches, including in vivo Massively Parallel Reporter Assays (MPRAs), to define the sequence basis and functional consequences of enhancer activity and to expand MPRA-based approaches to other
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) Application Deadline 31 May 2026 - 00:00 (UTC) Country Finland Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
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neurons using multi-omics, cis-regulatory variants will be mapped onto these enhancers and then their function determined by Massively Parallel Reporter Assays (MPRA). The research will involve stem cell
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computing (HPC) and parallel processing to enable the analysis of massive datasets. Experience in advanced statistical inference (e.g., Bayesian statistics, spectral methods) for extracting robust patterns
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crosslinks and how this pathway contributes to bacterial survival following antibiotic treatment. This work will be tightly coordinated with live-cell fluorescent microscopy approach undertaken in parallel in
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
projects using massively parallel reporter assays (MPRA) to quantify the impacts of disease-related genetic variants. Finally, they will interact with nearby collaborators to plan and analyze functional
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Participate in teaching and supervision activities, in line with the candidate’s profile and interests The research activities will be hosted by the Parallel Computing and Optimisation Group (PCOG) at SnT
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) experience in code development with parallel programming techniques using the message passing interface (MPI) library Proficiency in writing code with C, C++ and/or Python Ability to demonstrate strong written
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, Statistical Physics, Genome Annotation, and/or related fields Practical experience with High Performance Computing Systems as well as parallel/distributed programming Very good command of written and spoken
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
Knowledge in modeling and algorithms for large-scale ordinary differential equations (ODEs) and differential-algebraic equations (DAEs) Proficiency in a scientific programming language (e.g., C, C++, Fortran