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limited to, integrated cancer risk prediction model, cancer subtype discovery, genomic and epi-genomic data integration, single cell RNA-Seq data analysis, non-coding RNA data analysis, and other datasets
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systems, social sciences, epidemiology or other health-related fields. Demonstrated proficiency through previous developed analytical codes with R Language for Statistical Computing and/or Python The ideal
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for the long-term health of our code repositories and the versioning of models and data (Git, DVC, MLflow). Requirements: Education: Ph.D Degree in Computer Science, Engineering, Mathematics, Physics
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: Writing and testing of code. Planning of research & discussing research with collaborators. Writing papers, and giving presentations. Qualifications: PhD in Chemistry Before applying, please note that to
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codes such as ImpactX, GPT, or similar. ● Experience with common PIC codes used in LWFA research such as OSIRIS, FBPIC, or similar. Brief Description: The primary purpose of this position is to
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, will be given preferential consideration in the event of equal suitability and qualification in accordance with the provisions of the German Social Code IX. In case of further queries regarding gender
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learning in chemistry would be advantageous, as would familiarity with ML approaches for atomistic modelling (e.g., MACE, ACE, NequIP, PhysNet, reactive MD). Prior contributions to scientific code
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concentration (SSC) from remotely-sensed data. Includes coding automatic satellite data extraction and analysis macros for multiple satellite data repositories and building regressions for SSC 30%- 2D
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of code to conduct complex comparative genomics, implement HMM searching strategies and conduct phylogenetic analysis on a grand scale while making use of sophisticated phylogenetic methods (for example
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). • Assisting with coding and qualitative analysis using tools such as NVivo and LLMs (training provided if needed). • Contributing to literature reviews, research memos, and summaries. • Supporting project