Sort by
Refine Your Search
-
Category
-
Program
-
Employer
-
Field
-
Python, Matlab, and R, and good UNIX knowledge are essential skills, as well as familiarity with biological omics data analysis techniques. Admission Regulations for Doctoral Studies at Stockholm
-
at RISE Fiberlab (Hudiksvall), one of the leading specialty fiber R&D facilities in Europe. Hudiksvall is located around 4 hours away from Umeå by train. Both HCF preform preparation and fiber drawing
-
learning, deep learning and relevant software framework (R and Python) is highly desired. Very good oral and written communication skills in English are required. Emphasis will also be given on personal
-
language such as Python, R, C, or MATLAB Fluent in English for communication and scientific writing Merits: Knowledge and experience in: Data Science and Statistics Radio Frequency Digital Signal Processing
-
Lepidoptera and plant ecology Statistics and programming (e.g. in R) The application should consist of the following (all files in PDF-format): Curriculum vitae including publication list, Master [alternatively
-
from the doctoral-level education they will receive. Experience in the R programming language (or alike), statistical inference and the use of machine learning methods is a merit for the position. How
-
. Documented experience and interest in developing models coupling the dynamics of soil, plants, and the atmospheric boundary layer as well as strong quantitative and programming skills (in MatLab, R, Python, C
-
be considered if combined with advanced coursework in cell and molecular biology and genetics. Experience working in a Unix/Linux environment, as well as documented experience in R or Python, is
-
tools for end-to-end processing of next-generation sequencing data, from raw data to variant discovery (e.g., GATK pipeline). Experience with programming languages (e.g. bash, Python, and R). Experience
-
and/or transcriptomics data Practical experience of working in Python and/or R, and Git Practical experience of working in computational cluster environments Knowledge of tumor and immune biomarkers