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AI Engineer with less than a year in AI/ML & Data Science
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Master's student in Bioinformatics at Eberhard Karls University of Tübingen with hands-on experience in data management, computational analysis, and clinical workflows. Proficient in Python programming with expertise in processing large biological datasets and building AI-powered tools. Background in biotechnology combined with practical laboratory and pathology experience. Seeking opportunities in healthcare informatics, data analysis, or research support roles.
Eberhard Karls University of Tübingen
M.Sc. Bioinformatics · Computational Biology, Algorithms, Data Science, Machine Learning
October 1, 2025 – Present
Dr. A.P.J. Abdul Kalam Technical University
B.Tech Biotechnology · Microbiology, Genetics, Biochemistry, Immunology, Bioinformatics
July 1, 2020 – June 1, 2024
AI for Scientific Research
Bioinformatics RAG System Developer
January 1, 2025 – Present
India
Saraswathi Institute of Medical Sciences
Pathology Department Trainee
July 1, 2023 – September 1, 2023
India
Green Biosynthesis of Metallic Nanoparticles
January 1, 2023 – January 1, 2024
Developed sustainable ZnO nanoparticle synthesis using E. coli as a biological medium. Independently managed long-term research project with detailed documentation and protocol adherence.
Phylogenetic Analysis of SARS-CoV-2 Strains
January 1, 2022 – January 1, 2023
Conducted sequence alignment and evolutionary analysis using MEGA; processed large genomic datasets.
Cultural Fit Analysis
The candidate's academic background in Bioinformatics and Biotechnology, combined with experience in developing AI tools for scientific research, aligns well with roles focused on scientific innovation and data-driven solutions. The diversity of projects, from nanoparticle synthesis to phylogenetic analysis and RAG system development, indicates adaptability and a broad interest in applying computational methods to biological problems. However, the experience level is entry-level for an AI Engineer, which might require significant ramp-up in a fast-paced industry setting.
Soft Skills & Operational Fit
The candidate demonstrates a strong analytical mindset and meticulous attention to detail, as evidenced by their research projects and RAG system development. Their experience in a clinical environment suggests an ability to adhere to protocols and manage documentation. The 'excellent cross-cultural communication' listed as a strength indicates potential for good team collaboration, though this is not directly assessed by the provided data.