Freshers BSc & MSc Bioinformatics Jobs at Feathersoft
Job Title: Junior Bioinformatics Analyst
Company: Feathersoft
Location: Infopark, Kochi
Employment Type: Full-Time
Experience Required: 0–1 Year
Salary Range: ₹3.0 – ₹4.2 LPA (depending on skills, education, and interview performance)
Job Description
As a Junior Bioinformatics Analyst at Feathersoft, you will work with a multidisciplinary team to support the development and implementation of computational tools and workflows for biological data analysis. This is an exciting opportunity for recent graduates or early-career professionals interested in applying programming and AI to solve real-world biological problems.
Responsibilities:
• Collaborate with cross-functional teams to design, develop, and implement
computational biology software solutions.
• Analyze biological datasets using computational and statistical techniques.
• Develop and apply AI models for complex biological challenges.
• Assist in maintaining and optimizing existing bioinformatics tools and pipelines.
• Contribute to cloud-based solutions for data storage, analysis, and visualization.
• Participate in code reviews, testing, and documentation to support best practices in
software development.
Qualifications:
• Bachelor’s or Master’s degree in Bioinformatics, Computational Biology,
Biotechnology, or related disciplines.
• Solid understanding of bioinformatics concepts, biological data types, and analysis
pipelines.
• Proficiency in Python and/or R programming languages.
• Foundational knowledge of AI/ML techniques such as machine learning, deep
learning, or NLP.
• Experience from academic projects or internships related to bioinformatics or AI is a
plus.
• Strong problem-solving skills and a detail-oriented mindset.
• Excellent communication and teamwork abilities.
Preferred Experience:
• Experience working with genomic data, protein structure modeling, or molecular
simulations.
• Hands-on with AI in bioinformatics, including sequence analysis or predictive
modeling.
• Familiarity with tools and databases like BLAST, GenBank, PDB, etc.
• Exposure to cloud platforms (AWS, GCP, Azure) for computational biology tasks.
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