
Állás
· Mid-level
Bioinformatics Scientist
Egyéb
• Mid-level
• Remote
• Teljes munkaidő
•
EU/EMEA
Role Title: Bioinformatics Scientist Role Type: Contractor Location: Remote micro1 is engaging Bioinformatics Scientists to contribute their specialized expertise to a customer's innovative project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters. Scope of Work Analyze complex datasets related to medicinal chemistry using advanced bioinformatics methodologies. Provide detailed scientific input and content to support the development and training of AI models. Curate, annotate, and validate datasets relevant to drug discovery and molecular analysis. Evaluate and synthesize findings from biological, chemical, and clinical data sources. Offer subject matter expertise on experimental design and data interpretation within medicinal chemistry. Assess AI-generated outputs for scientific accuracy, relevance, and reliability. Deliver comprehensive written feedback and actionable recommendations for model improvement. Preferred Qualifications Advanced degree (e.g., PhD or MSc) in Bioinformatics, Computational Biology, Medicinal Chemistry, or a related discipline. In-depth knowledge of medicinal chemistry concepts, including structure-activity relationships and drug design principles. Demonstrated experience in handling and interpreting large-scale omics or cheminformatics datasets. Familiarity with software tools, databases, and programming languages commonly used in bioinformatics (e.g., Python, R, RDKit, KNIME). Strong scientific communication skills, with the ability to clearly articulate complex ideas and technical concepts. Proven track record of contributing to research projects at the intersection of biology, chemistry, and data science. Experience collaborating in multidisciplinary or remote project environments is advantageous. Originally posted on Himalayas
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PPMI
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