COMPUTATIONAL SCIENTIST SKILLS, EXPERIENCE, AND JOB REQUIREMENTS
Updated: Dec 24, 2024 - The Computational Scientist possesses extensive experience in applied mathematics, computer science, and specific scientific disciplines, with a strong background in developing application codes and libraries for high-performance computing resources. This role requires expertise in numerical methods, parallel algorithms, and programming languages, along with proficiency in parallel software development on large-scale computational resources. The scientist also can work with prominent simulation codes, leadership computing facilities, and an in-depth understanding of the entire software stack on leadership computing platforms, complemented by excellent communication, organizational, and interpersonal skills.
Essential Hard and Soft Skills for a Standout Computational Scientist Resume
- Applied Mathematics
- Numerical Methods
- Parallel Algorithms
- MPI
- Fortran
- C
- C++
- High-Performance Computing
- Simulation Codes
- Scientific Computing Libraries
- Communication
- Teamwork
- Problem-Solving
- Critical Thinking
- Adaptability
- Interpersonal Skills
- Time Management
- Organizational Skills
- Leadership
- Motivation
Summary of Computational Scientist Knowledge and Qualifications on Resume
1. BS in Computer Science with 5 years of Experience
- Knowledge of genomics (such as genome assembly, annotation, pangenome, comparative genomics, functional genomics, etc)
- Experience in data integration, data mining, using and/or managing databases
- Experience working with UNIX/LINUX environment
- Experience with machine learning, and natural language processing
- Proficiency in applying statistical methods (such as differential expression analysis, gene network analysis, gene set enrichment analysis, integrated omics analyses, etc.)
- Proficiency in one or more statistical programming or scripting languages such as R, Python, or other relevant languages
- Demonstrated ability to prioritize multiple tasks
- Ability to learn and develop new technical skills, and expand knowledge
- Excellent communication skills, fluency in both verbal and written English communication
- Ability to drive the application of computational analysis for trait lead discovery
2. BS in Applied Mathematics with 3 years of Experience
- Theoretical knowledge of bioinformatics, and computational biology
- Keeps current with emerging trends in bioinformatics and computational biology
- Familiarity with popular public domain data sources and programmatic interfaces
- Experience in designing and conducting computational biology activities to meet program objectives
- Able to provide input on timelines and resource needs as indicated
- Able to evaluate/develop computational methods based on project needs
- Basic knowledge of biomedical science and technologies outside the specific discipline
- The ability to independently manage own workload
- Must be scientifically independent
- Ability to search literature and come up with innovative solutions to difficult problems
3. BS in Physics with 5 years of Experience
- Experience in successful and modern software design and development and lifestyle methods.
- Python and C programming experience
- Experience working in multidisciplinary scientific collaboration
- Track record of producing high-quality software on schedule
- Appreciation for a range of scientific domains: high-energy physics, bimolecular, climate sciences, etc.
- Experience working in inter-disciplinary teams
- A degree in CS/CE in high-performance computing
- Experience in system software design and implementation of scalable systems
- The ability to conduct scientific presentations to internal audiences
- Able to determine methods on new assignments, perform a literature search to propose innovative solutions
4. BS in Computational Science with 4 years of Experience
- Experience in applied mathematics, physics, or other math-intensive subjects.
- Experience developing advanced data analysis techniques, signal processing algorithms, or control algorithms.
- Advanced coding and simulation skills.
- Ability to translate ideas from research articles to functioning prototypes.
- Practical knowledge and proven skills in areas such as convex optimization, dimensionality reduction, compressive sensing, computational imaging, high-dimensional signal processing, etc.
- Depth of experience in several different signal domains (audio, RF, images, tomography, etc.)
- Ability to prototype algorithms in numerical environments (MATLAB, Python, Julia, etc.) as well as translate them into practical implementations (Python/Numpy/Scipy, C/C++, etc).
- Experience in developing and optimizing algorithms to run on DSP/GPU/SIMD architectures.
- Hands-on prototyping skills with electronics and embedded computing.
- Excellent leadership, interpersonal, and communication skills
5. BS in Engineering with 6 years of Experience
- Experience working with analytical models, methods, applications, and tools, such as statistical analysis, predictive modeling, simulation, machine learning, and artificial intelligence
- The ability to select and apply the appropriate analytical techniques
- Analyzing large and complex data sets, with a strong aptitude for conducting quantitative and qualitative analysis
- Knowledge of “Big data” environment including Hadoop, Spark, Hive, Netezza
- A good working knowledge of programming in Spark - Scala, PySpark, SparkR
- A good working knowledge of programming in R, Python, SAS, or Java
- A good working knowledge of visualization skills such as Tableau, Power BI, or R Shiny
- Able to contribute to a positive working environment by building strong, collaborative relationships with team members
- The ability to communicate effectively to various audiences, including various levels of management and external clients, in a professional environment
- Demonstrate flexibility in prioritizing and completing tasks, communicating potential conflicts to a supervisor
6. BS in Data Science with 8 years of Experience
- Knowledge of and experience with machine learning and bioinformatic techniques.
- Experience with high dimensional data analysis derived from Next Generation Sequencing, including some of the following microbiome data, RNASeq, DNASeq, miRNA, copy number, epigenetics, and single-cell sequencing
- Hands-on experience developing and implementing bioinformatic pipelines for microbiome data analysis, RNASeq, DNASeq, single-cell datasets, and metabolomics.
- Solid knowledge of Unix/Linux, command line interfaces, and fluency in some common scripting and/or programming languages (e.g., R, Python, Perl, Java, C / C++).
- Familiarity with parallel computing, relational databases (e.g., SQL), and cloud computing or distributed computing (i.e. AWS)
- Familiarity with Tensorflow/Keras or equivalent deep-learning language
- Strong scientific understanding of molecular biology and genomics
- Excellent problem-solving, communication, presentation, and interpersonal skills
- Independent, self-starting and supportive of team-based research and able to work effectively in a matrix organization
- Ability to work in a team and influence the team to make data-driven decisions
7. BS in Bioinformatics with 5 years of Experience
- Experience in applied mathematics, computer science, or a specific scientific discipline
- Demonstrate experience developing application codes and/or libraries for high-performance computing resources.
- Experience with numerical methods, parallel algorithms, MPI, and a common scientific computing programming language (i.e., Fortran, C, and/or C++).
- A good working knowledge of Parallel software development on large-scale computational resources.
- Experience with one or more prominent simulation codes or libraries that use the Leadership Computing Facilities.
- Experience in a domain aligned with US DOE Office of Science mission areas.
- Experience with multiple common scientific computing programming languages and programming models.
- Experience with computing at scale (for example, computing on a resource in the top 20 of the Top500 list).
- Knowledge of the entire software stack on a leadership computing platform, including compilers and runtime systems.
- The ability to work in a dynamic, team environment
- Excellent interpersonal skills, oral and written communication skills, organizational skills, and strong personal motivation