Duration: Full time. Danilo holds an M.S. Ph.D. in Statistical Genetics, Computational Biology, Biological Sciences, Genetics, Computer Science, Statistics or related field. Title: Computational Biologist - Statistical Geneticist. and Ph.D. degree in Genetics and Plant Breeding having an extensive background in potato, maize, and wheat breeding/genomics. The identification of causes of genetic diseases has been carried out by several approaches with increasing complexity. Previous postdoctoral experience in the area of computational genomics or statistical genetics is preferred. Statistical geneticists at SPH develop statistical methods for understanding the genetic basis of human diseases and traits. The successful candidate will be responsible for developing new statistical and computational genetics/genomic methods for understanding and integrating association studies (GWAS), genetic screen perturbations, and transcriptome data. 3. Minimum number of years and relevant work experience. Dr. Lin’s major statistical research interests lie in developing statistical methods for high-dimensional and correlated data. Welcome back. 2. Students take courses in human and population genetics, biostatistics, epidemiology, statistical genetics, and computational modeling. Author information: (1)Department of Medical Sciences and Science for Life Laboratory, Uppsala University, Uppsala, Sweden. This area of research is concerned with diseases and traits that have a complex or mixed inheritance background, influenced by external environmental effects and their interactions with genes. Computational and Statistical Genetics Conference scheduled on June 10-11, 2022 in June 2022 in Barcelona is for the researchers, scientists, scholars, engineers, academic, scientific and university practitioners to present research activities that might want to attend events, meetings, seminars, congresses, workshops, summit, and symposiums. Department: Global IT Solution Center. Location: Mississauga Head Office. I will present allele specific methods we developed to validate the computational predictions and to identify changes of the genetic effects on gene expression across different environmental conditions. Candidates with a degree in biological sciences are also encouraged to apply if they have demonstrated experience in computational or statistical work. Statistical Genetics and Computational Biology The Huang lab develops cutting-edge computational methods to tackle problems arising from the human genetics research. Research Areas: Bioinformatics, Computational Genomics, Computational Systems Biology, Statistical and Population Genetics Research Interests: The Rau lab utilizes populations of mice to study the transcriptomic and epigenomic landscape underlying cardiovascular disorders using a combination of wet and dry-lab techniques. The Human and Statistical Genetics Ph.D. Statistical and computational approaches for finding genes underlying complex disease and quantitative phentoypes. Modeling genetic networks and developmental pathways. Job requirements: – Kind, curious, and ambitious researcher. PhD in Statistical Genetics, Genetic Epidemiology, Computational Biology, Bioinformatics, Mathematics, Statistics or related fields; Five or more years of experience in statistical genetics or relevant fields; A working knowledge of applied mathematics or statistics to analyze large-scale human genetics … Objectives: Learn statistical computational techniques in Statistical Genetics/Genetic Epidemiology, emphasizing statistical models, algorithms and programming. Sign in to save Research Fellow - Computational Genomics and Statistical Genetics at Massachusetts General Physicians Organization (MGPO). (2)Department of Medical Sciences, Uppsala University, Uppsala, Sweden. 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