Computational Scientist Jobs

Master's or PhD in physics, operations research, computer science, or electrical engineering (or equivalent experience)

Experience in solving complex computational problems using advanced operations research / computer science techniques, including decomposition algorithms, dynamic programming, heuristics, etc.

Experience in modeling, benchmarking and optimizing real-world industry problems

Strong programming skills (e.g., Python, Rust, C/C++)

Experience with high performance computing

Develop and expand high performance computing infrastructure to run computational experiments and simulations

Work with other scientists, clinicians, computational biologists, project managers, and external partners to accomplish our mission of curing diseases

Experience in Research & Development of discovery or translational programs

Entrepreneurial mindset, experience in startup environment preferred a plus

Work in a structure-based computationally driven drug discovery paradigm

Work with DepMap and other open data sources to drive our target identification workstreams

Iteratively scale, rethink, and collaborate on a drug discovery engine that will scale to hundreds of programs

Implement appropriate project management practices and frameworks to computational chemistry project

Write well-structured, informative, and easy-to-read documents to guide the team and share knowledge with stakeholders

Work with other scientists, clinicians, computational biologists, project managers, and external partners to accomplish our mission of curing diseases

3-5 years of experience in computational chemistry

Entrepreneurial mindset, experience in startup environment preferred a plus

Lead a team of 3+ Computational Chemists in running AI-enabled computational workflows for drug discovery

Proficiency in biological database management and the use of bioinformatics tools and software

Experience in data governance modeling

Experience working with HTS Omics sequencing data (Eg: RNAseq, scRNAseq, ISLAND, WES)

Experience supporting and working with cross-functional teams in a dynamic environment

Experience working with high-throughput sequencing data (RNAseq, scRNAseq, WES)

Extensive knowledge in applying machine learning and statistical modeling to biological datasets

Analyze data on the impact of existing or proposed management or public practices on biology resources

Conduct literature review to learn new statistical and programming skills relevant to research project

·Computational and analytical skills, including proficiency with R

·Excellent communication, advanced English reading, writing, listening and speaking skills

·Excellent presentational skills, capable of conveying technical information in a clear and thorough manner

·Excellent organizational skills with great attention to detail in coding practices

(d) Documented experience with omics data analysis and related bioinformatics tools and libraries.

(f) Excellent communication, advanced English reading, writing, listening, and speaking skills.

(b) Proficiency in Unix/Linux and in R/python.

(c) History of scientific authorship.

(i) NGS analysis (e.g. mutation calling, DNAseq/RNAseq)

(ii) Package development in R or Python (e.g. Bioconductor)

(d) Documented experience with omics data analysis and related bioinformatics tools and libraries.

(f) Excellent communication, advanced English reading, writing, listening and speaking skills.

(b) Proficiency in Unix/Linux and in R/python.

(c) History of scientific authorship.

Minimum of a Master's Degree in Computational Biology, Bioinformatics, Bioengineering or related sciences. PhD and post-doctoral experience preferred.

Documented experience with omics data analysis and related bioinformatics tools and libraries.

Excellent communication, advanced English reading, writing, listening and speaking skills.

GRED Research team is looking for a computational biologist/bioinformatician that can support them with developing Neoantigen prediction/prioritization algorithms.

Proficiency in Unix/Linux and in R/python.

Good understanding of biological concepts and experimental methods commonly used in molecular biology and interest to learn more.

Practical experience with analog simulation, place & route engines, or various analog and discrete optimization methods

Program in Python and C++

Improve our current engines and develop new analysis and optimization engines

Integrate and connect these engines to our existing service and build the interfaces of our web applications

Write automated tests and debug customer problems

Academic background in linear algebra, calculus, computational geometry, statistics, control theory, optimization, numerical algorithms

Demonstrated knowledge in a wide range of computational chemistry methods

Demonstrated experience closely collaborating with experimental teams

Demonstrated experience in the use of molecular (Q-Chem, Gaussian, etc.) and/or solid-state (Siesta, VASP, etc.) DFT packages

Demonstrated experience using molecular dynamics simulations involving radical reactive intermediates, conformation sampling of molecules on surfaces, and/or reactive surface chemistry

Breadth of knowledge in computational methods ranging from molecular mechanics to highly-correlated electronic structure theory

Experimental knowledge in the areas of STM/AFM, organic synthesis, or nanosystems

A PhD in a quantitative discipline (e.g. Computational Biology, Computer Science, Applied Mathematics, Statistics, Biostatistics or Physics), or equivalent experience.

Working knowledge in machine learning modelling (e.g. neural networks, Bayesian methods, random forests, clustering).Proficient in Python or R

Post-graduate experience (postdoc or industry)

Experience with RNA biology or antisense oligonucleotides

A wide array of company-paid benefits

Aid the design of wet-lab experiments to investigate novel and existing RNA regulatory mechanisms

Working knowledge of antibody structure and function

Excellent programming skills (Python preferred)

Strong interpersonal skills with the ability to work collaboratively as a member of cross-functional team

Excellent verbal and written communication skills, including public presentation of complex data

Collaborating with teams across the company to understand engineering challenges and propose solutions

Preparing and authoring materials to educate colleagues, and communicate strategies, key findings and implications

PhD, or MS + 3 years experience, in systems biology, genomics, cancer biology, or related discipline

Experience with single-cell RNA-seq data analysis and interpretation

Solid knowledge of cancer biology

Experience with drug screening data

Hybrid remote / onsite workplace

Familiarity with common bioinformatics, biostatistics and data analysis practices and tools

Develop, improve and maintain full-stack solutions for data management and storage in consultation with other developers

Demonstrates a commitment to enhancing one’s own awareness, knowledge, and skills related to equity, diversity, and inclusion

Excellent verbal and written communication skills

Comfortable working in a Unix environment, including experience with shell scripting and common command-line tools

Demonstrated interpersonal skills including the ability to work effectively with others in a team environment

Experience in HPC and cloud computing in an academic setting