Computational Biologist
- Employer
- VantAI
- Location
- New York, Iowa, US
- Salary
- Competitive
- Closing date
- Dec 9, 2021
View more
- Sector
- Academic / Research
- Field
- Informatics / GIS
- Discipline
- Modeling
- Salary Type
- Salary
- Employment Type
- Full time
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About VantAI:
VantAI is building a computational pipeline combining state-of-the-art physics-based modeling and machine learning to revolutionize drug discovery and development. Working together with some of the world's leading biopharmaceutical companies, we design, test, and optimize novel therapies to treat some of the world's most difficult diseases.
Key Responsibilities:
Requirements:
VantAI is building a computational pipeline combining state-of-the-art physics-based modeling and machine learning to revolutionize drug discovery and development. Working together with some of the world's leading biopharmaceutical companies, we design, test, and optimize novel therapies to treat some of the world's most difficult diseases.
Key Responsibilities:
- Develop innovative approaches and algorithmsthat disrupt key steps in the R&D process using large-scale bioinformatics data
- Merge state-of-the-art in silico approaches with cutting-edge machine learning ( e.g. , deep learning, generative methods, reinforcement learning, topology)
- Work collaboratively with experts from other fields ( e.g. , molecular biology, medicinal chemistry, computational chemistry, machine learning) to drive harmonized models with innovative features
Requirements:
- MS/PhD degree in Computational Biology, Bioinformatics, Systems Biology, Bioengineering, Pharmacology, Biochemistry, Biophysics, or other related subject (we will also consider BS degrees in these areas for candidates highly qualified across all other requirements or with significant work experience)
- Deep content knowledge and experience at the intersection between biology and computer science
- Track record of developing new methods, tools, or programs in or related to computational biology
- Exposure to R&D workflows, software, and decision making ( e.g., gene prioritization, network science) is highly preferred
- Exposure to scientific research is highly preferred
- Deep expertise in one or more of the following methodological spaces: NGS/genomics/genetics/genome topology/mutation interpretation; transcriptomics/RNA-seq/scRNA-seq/splicing, etc.; epigenetics/epigenomics; systems biology, network pharmacology, molecular signaling, etc.; structural biology, structural informatics, biophysics, molecular dynamics, etc.; bioinformatics/biomedical informatics
- Competent in several programming languages: experience in Python, R, and state-of-the-art machine learning frameworks such as PyTorch and PyMC3/Tensorflow Probability is highly preferred
- Experience working in distributed and cloud environments including GPUs is preferred
- Experience working in Linux/UNIX environment
- Quick and scrappy learner who adapts well to a fast-moving environment and gets things done, combining creativity, problem-solving skills, and a can-do attitude to overcome any obstacle
- Understanding of business problems and how to build end-to-end analytics use cases tied to business value
- Ability to provide thought leadership by researching best practices, conducting experiments, and collaborating with industry leaders
- Excellent written and verbal communication skills along with a strong desire to work in cross-functional teams
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