Company Description

Bio-Silicon Labs is a pioneering organization offering cutting-edge bioinformatics and advanced research services. Our expertise encompasses next-generation sequencing (NGS)-based solutions, including RNA-Seq, genomics, epigenetics, and personalized medicine. We excel in innovative areas such as AI, machine learning (ML), deep learning (DL), quantum computing, drug discovery, and space biotechnology. With a dedication to excellence, we use leading-edge technologies like Illumina, Nanopore, and PackBio platforms to support diverse scientific domains, from human genetics to microbiome research. Bio-Silicon Labs emphasizes fostering sustainable scientific advancements with high-quality, impactful solutions.

Role Description

This is a full-time hybrid role for a Scientist at Bio-Silicon Labs, located in EU & India, with partial work-from-home flexibility. Responsibilities include designing and conducting experiments, analyzing complex datasets using modern bioinformatics methodologies, and contributing to ongoing projects in areas such as genomics, molecular simulations, and AI/ML model development. The Scientist will work collaboratively with interdisciplinary teams and provide insights to drive innovation across domains like quantum computing, brain-computer interfaces, and extended reality simulations.

Qualifications

• Strong expertise in bioinformatics, genomics, and next-generation sequencing (NGS) methodologies, including RNA-Seq, WGS, and variant calling.
• Proficiency in programming, data analysis, and machine learning, with experience in AI/DL/ML model development and tools for automation and containerization.
• Understanding of molecular docking, dynamic simulations, and advanced drug discovery processes.
• Experience with genetic testing, chromosomal analysis, and associated human genetics fields (e.g., NIPT, PGT).
• Familiarity with advanced research areas like quantum computing in bioinformatics and space biotechnology.
• Outstanding problem-solving abilities, critical thinking, and collaborative teamwork skills.
• Bioinformatics, Computational Biology, or a related field is strongly preferred. Candidates with equivalent professional knowledge will also be considered.