What are the responsibilities and job description for the Vice President Computational Biology & Machine Learning position at SciPro?
Vice President of Computational Biology and Machine Learning
A VC backed biotech is looking for Head of Computational Biology and Machine Learning to lead a multidisciplinary team in the development and application of machine learning methodologies to protein design.
The ideal candidate will have a strong background in both computational biology and machine learning, with hands-on experience applying these technologies to solve complex protein engineering challenges. In addition to technical expertise, they are looking for a leader who can manage, mentor, and grow a dynamic team of scientists and engineers, while collaborating with cross-functional teams to shape strategic initiatives.
Key Responsibilities:
- Lead the development and implementation of machine learning algorithms and models to optimize protein design workflows, including structure prediction, stability analysis, and functional prediction.
- Drive innovation in computational biology through the application of state-of-the-art machine learning methods to address protein design and optimization challenges.
- Oversee a talented team of computational biologists, data scientists, and machine learning engineers; provide mentorship, guidance, and career development.
- Collaborate with experimental biologists, chemists, and software engineers to ensure seamless integration of computational insights into experimental workflows.
- Identify and prioritize key projects that will have the highest impact on the company's protein design capabilities.
- Present research findings, technical reports, and project updates to internal stakeholders, including senior leadership.
- Stay up to date with the latest developments in computational biology, machine learning, and protein engineering to guide the team toward innovative solutions.
Qualifications:
- Ph.D. or equivalent in Computational Biology, Bioinformatics, Machine Learning, or a related field.
- 8 years of experience in computational biology and protein design, with a proven track record of applying machine learning techniques to protein engineering problems.
- Strong knowledge of protein structure, folding, and function, with experience in designing algorithms for protein sequence-structure-function relationships.
- Extensive experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and bioinformatics tools.
- Proven leadership experience, including managing teams of scientists and engineers, and driving complex, cross-functional projects.
- Expertise in software development, algorithm optimization, and large-scale data analysis.
- Excellent problem-solving, communication, and interpersonal skills.
- A passion for applying innovative technologies to solve real-world biological challenges.
