Intermediate (2-5 years of experience)
Summary of the Role
The Bioinformatics Scientist will be responsible for analyzing complex biological data and contributing to the development of algorithms and computational methods to address a variety of biological challenges. The candidate should have a background in bioinformatics, computational biology, or a related field, and possess practical experience with bioinformatics tools and databases.
Required Skills
Proficiency in one or more programming languages such as Python, R, or Java.
Strong analytical and problem-solving skills.
Ability to work independently and collaboratively in a fast-paced research environment.
Excellent communication and presentation skills.
Solid understanding of molecular biology concepts.
Experience with machine learning techniques and their applications in bioinformatics.
Qualifications
Master's degree in Bioinformatics, Computational Biology, Computer Science, or a related field.
2-5 years of experience in bioinformatics or a closely related field.
Experience with bioinformatics tools and databases such as BLAST, Biopython, R, and others.
Familiarity with next-generation sequencing data analysis and associated software tools.
Strong background in statistical analysis and proficiency with statistical software.
Ability to communicate complex information to a non-technical audience.
Responsibilities
Analyze and interpret large datasets such as genomic, transcriptomic, proteomic, and other biological datasets.
Develop and apply computational tools and algorithms for the processing and analysis of biological data.
Collaborate with interdisciplinary teams including biologists, computational scientists, and software developers.
Maintain current knowledge of the latest bioinformatics and computational biology techniques and tools.
Prepare and present findings in both technical reports and scientific publications.
Participate in the design and execution of bioinformatics research projects.
Provide bioinformatics support to experimental teams and assist in data analysis.
Ensure data quality and reproducibility of the computational analyses.