Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
. Development of pipelines and applications for data quality control of affinity based proteomic data. Analyzing data from internal validations of new laboratory methods, bioinformatics tools and interlaboratory
-
UNIX filesystems from the command line, working in conda environment, installation and implementation of packages from github, batch job submissions in clusters Further details The position is funded
-
quality controls for sequencing, and document and evaluate results. Analysis of ancient and historical plant, sediment and other types of samples also occurs. The tasks also include discussing, implementing
-
include e.g. data quality controls, mapping of DNA data to reference genomes, investigation of deamination patterns, analysis of sex chromosomes, analysis of mitochondrial and Y-chromosome haplogroups
-
analyses, version control) is an advantage We attach great importance to personal qualities in this recruitment. As a person, you are analytical, structured, detail-oriented, and committed to high-quality
-
using relevant metadata standards, ontologies and controlled vocabularies. Experience with international repositories for the deposition and publication of Life Science data. Familiarity with principles
-
Linux command-line environment and on high performance computer clusters Excellent communication skills in both written and spoken English are required, as is ability to collaborate with scientists
-
qualifications. For specific eligibility, applicants must also have a good command of spoken and written English. The benchmark is 550 points on the TOEFL test (or 213 points on the TOEFL-CBT, or 79 points
-
years of experience in systems development with Python and version control systems, e.g., Git – Documented experience with using container and cloud technologies such as Docker, Helm, and Kubernetes
-
large-scale clinical, laboratory, registry, or other health-related data (experience with Nordic registry data is a plus). Familiarity with biomedical ontologies, controlled vocabularies, or coding