Computational Biology Software Engineer

Columbia University in the City of New York; New York (NY); In loco; USD 72.000 - 88.000; Tempo pieno

Descrizione del lavoro

The AlQuraishi Lab at Columbia University is seeking a full-time Programmer with a strong focus on software engineering and computational biology. The role involves developing and maintaining software tools to analyze signaling networks in mammalian systems.

You will work at the intersection of software engineering, machine learning, and computational biology, collaborating with lab members and partners across OpenFold, AISB, and OpenBind on large-scale datasets and analyses.

Competenze

• Bachelor’s Degree in Computer Science, Computational Biology, Bioinformatics, Mathematics, related quantitative field, or equivalent in education and experience.
• At least 3 years of related experience.
• Experience with machine learning, scientific computing, computational biology, bioinformatic, or structural biology.

Mansioni

• Write code and develop machine learning algorithms
• Run large scale analyses
• Summarize and prepare reports on the findings
• Utilize analytical skills to solve moderately complex problems based on guidelines, protocols, and procedures
• Work within guidelines to carry out assigned duties
• Share information and confirmation of data with other members of the lab and the PI

Conoscenze

Machine learning experience

Statistical methods

Independent project delivery

Formazione

Bachelor’s Degree in Computer Science, Computational Biology, Bioinformatics, Mathematics, related quantitative field, or equivalent

Descrizione del lavoro

The AlQuraishi Lab at Columbia University is seeking a full-time Programmer with a strong focus on software engineering and computational biology. The role involves developing and maintaining software tools to analyze signaling networks in mammalian systems.

You will work at the intersection of software engineering, machine learning, and computational biology, collaborating with lab members and partners across OpenFold, AISB, and OpenBind on large-scale datasets and analyses.