PhD - Bioinformatics Engineer (LLM/ AI) - 100% REMOTE

Job Title: Bioinformatics Data Engineer 

 Looking for someone who is a recent graduate(PhD) with 5 years of experience

• We are seeking a Bioinformatics Data Engineer to spearhead the development of an AI-first ecosystem aimed at transforming the drug discovery landscape.
• This role demands a proactive individual with a profound understanding of machine learning, AI, and bioinformatics, poised to deliver innovative solutions that accelerate the validation and identification of novel drugs.
• The ideal candidate will have extensive experience in managing and analyzing large-scale biological data, understanding its intricacies, and using this data to train robust machine learning models.

Key Responsibilities:

• Architect and Develop AI-Driven Ecosystems: Design and develop an advanced AI-driven data ecosystem to facilitate efficient and accurate drug target discovery.
• Implement Scalable Machine Learning Models: Design and implement scalable machine learning models and data pipelines to analyze complex biological datasets, including genomic, transcriptomic, and imaging data.
• Cloud Platform Utilization: Utilize modern cloud platforms to deploy machine learning solutions and manage large-scale data storage and computation.
• Advanced AI Techniques: Innovate and apply state-of-the-art AI techniques, including deep neural networks, to extract insights from large and diverse datasets.
• Collaborate on Drug Discovery Strategies: Work with interdisciplinary teams to translate experimental data into actionable drug discovery strategies.
• Continuous Technology Integration: Stay at the forefront of AI, machine learning, and bioinformatics, continuously integrating new technologies and methodologies to enhance data-driven decision-making.

Minimum Qualifications:

• Educational Background: PhD in Computer Science, Bioinformatics, Statistics, or a related quantitative field.
• Machine Learning Expertise: Solid experience with AI and machine learning tools and frameworks.
• Programming Proficiency: Proficient in Python and R, with a strong track record of developing and deploying applications in a cloud environment.
• Experience with Biological Datasets: Demonstrated ability in handling complex biological datasets, including consortium and atlas-type data, and applying advanced statistical and machine learning methods to solve real-world problems.

Preferred Skills:

• Data Handling Expertise: Extensive experience in data harmonization, normalization, and preprocessing of large-scale biological datasets to ensure their readiness for machine learning applications.
• Understanding of Biological Data Nuances: Deep understanding of the nature, limitations, and pitfalls of biological datasets and the ability to apply this knowledge systematically in data cleaning and management.
• Advanced Machine Learning Techniques: Expertise in genetic algorithms, ensemble methods, and unsupervised learning techniques, with a focus on their application to biological data.
• Analytical Skills: Excellent analytical skills, with the ability to see beyond the numbers to the strategic implications of the data.
• Collaboration and Communication: Strong communication and collaboration skills, with experience working in agile, cross-functional teams.
• Passion for Innovation: A strong passion for using AI to drive innovations in health technology and drug discovery.