Kernal is creating mRNA 2.0 therapies that work in specific cells
Senior Computational Biologist
Kernal Bio is a VC-backed Biotech company that is creating mRNA drugs that instruct specific cells in the body on how to make their own medicine. Messenger RNA technology has proven extremely useful in rapidly developing vaccines against COVID-19. Kernal Bio is developing the next generation of mRNA therapy, called mRNA 2.0. It solves a critical problem of cancer cell selectivity that affects many oncology drugs. Located in Cambridge, MA, Kernal Bio received three awards from Amgen and NASA. With roots at MIT, Harvard, and biopharma industry, Kernal Bio’s interdisciplinary team of MDs and PhDs previously built a successful Biotech company and has deep expertise in nucleic acid-based therapeutics and immuno-oncology space.
Kernal is seeking a highly motivated computational biologist. The successful candidate will join a team of bioinformaticians and data scientists to identify actionable mRNA sequence features for next-generation therapeutics. The successful candidate must be able to work in a fast paced and highly dynamic Biotech environment. Ideal candidate will be a great team player with excellent communication skills.
Work independently and think out of the box to extract meaningful insights from public datasets Apply advanced statistical methods to cross-validate and evaluate significance of hypotheses Work collaboratively with internal and external cross-functional teams, collaborators, and SAB members to align, plan and execute on the overall research and development plans Present scientific findings internally and externally at key scientific conferences Support IP filings and manuscript preparations Creatively use network biology tools to identify novel targets for wet lab scientists
Ph.D. in Computational Biology/Bioinformatics with 1+ years of Biopharma experience Experience with NGS data, genomics, transcriptomics, proteomics analyses, bash/shell scripting, public datasets, such as TCGA and GTEX, RNA folding Fluency in commonly used programming languages in common computational biology tools, such as Python, R, Perl or C/C++ Good understanding of capabilities and limits of the modern machine learning techniques such as Deep Neural Networks, CNNs, GANs, LSTMs, and expert knowledge in at least one deep learning framework such TensorFlow or PyTorch Familiarity with the heuristic search and multi-objective optimization algorithms such as gradient descent, A-star, genetic algorithms, Bayesian optimization, etc. Eagerness to learn new methods Excellent communication and time management skills Ability to manage multiple projects Attention to detail
Preferred skills: Theoretical understanding ribosome profiling and network biology, hands on expertise on single-cell transcriptomics, proteomics analyses, massively parallel reporter assays, workflow management, AWS, Azure, or Google Cloud, RNA folding, pathway analysis, and/or machine learning and data visualization experience on biological datasets
Highly competitive 401(k)
Highly competitive healthcare coverage
Competitive paid time-off policy On-site subsidized cafeteria
Free parking, monthly subway pass or a subsidized commuter rail pass
Free MIT Athletic Membership
Free Bluebikes Membership
Flexible Spending Account Paid parental leave, family caregiver leave, medical leave
Paid insurance coverage
Kernal Bio is dedicated to providing a diverse work environment and is committed to equal employment opportunity for all its employees and qualified applicants. We do not discriminate in employment practices for reasons of race, color, national origin, age, gender, sexual orientation, marital or veteran status, religion, disability, or any other legally protected status. Kernal Bio will make reasonable accommodations for qualified individuals with known disabilities, in accordance with applicable law.
Click Here to Apply: https://www.kernalbio.com/careers
Kernal is creating mRNA therapies that instruct specific cells on how to make their own drugs to cure an illness. Today, we are targeting cancer, but this platform can be used for a number of other illnesses, too. With roots at MIT, Harvard and Bio Pharma, the team previously built a successful Biotech company and has deep technical expertise in mRNA and oncology space.