Computational Biologist
Science & Research
Computational Biologists create models and algorithms to understand complex biological processes. They may work in genomics, systems biology, drug discovery, biotechnology and biomedical research, often collaborating with laboratory scientists.
Salary (Nigeria)
₦3M–₦12M
Exam requirements
Career pathway
Biology / Biological Sciences Degree
4 years
Build foundational knowledge in genetics, molecular biology, cell biology, and biological systems.
Biochemistry Degree
4 years
Develop knowledge of biological molecules and biochemical processes relevant to computational research.
Biotechnology Degree
4 years
Study genetics, molecular biology, biotechnology, and laboratory applications.
Computer Science Degree
4 years
Develop programming, algorithms, computational theory, and data-processing skills.
Mathematics / Statistics Degree
4 years
Build strong quantitative foundations for biological modelling and statistical analysis.
Computational Biology Certification
3-12 months
Gain practical skills in computational modelling, biological data analysis, and programming.
Bioinformatics Training
3-12 months
Develop expertise in sequence analysis, genomics, biological databases, and computational tools.
Computational Biology Research Internship
3-12 months
Gain practical research experience using computational approaches to solve biological problems.
Master's in Computational Biology / Bioinformatics
1-2 years
Develop advanced expertise in computational modelling, genomics, statistics, and biological data science.
Computational Biology Scientist → Senior Scientist → Research Lead
3-8 years
Progress from analytical and research positions into advanced scientific and research leadership roles.
Common challenges
Handling Large & Complex Biological Datasets
DifficultGenomic and molecular datasets can be extremely large and computationally demanding.
How to handle: Learn efficient programming, databases, cloud computing, high-performance computing, and data-management techniques.
Building Accurate Biological Models
DifficultThe field requires simultaneous understanding of complex biological concepts, mathematics, statistics, and programming.
How to handle: Build expertise progressively and work on interdisciplinary projects that combine multiple areas.
Building Accurate Biological Models
ModerateBiological systems are highly complex, making it difficult to represent every relevant factor computationally.
How to handle: Develop strong mathematical modelling, statistics, validation, and experimental-design skills.
Reproducibility of Research
ModerateDifferent software versions, datasets, pipelines, or analytical choices can produce different results.
How to handle: Use version control, documented workflows, reproducible environments, and well-maintained computational pipelines.
Rapidly Changing Tools
ManageableNew algorithms, databases, sequencing technologies, and computational tools appear regularly
How to handle: Follow scientific literature, technical communities, and continuing education programmes.
Communicating Across Disciplines
ManageableComputational researchers may need to explain technical results to laboratory scientists or healthcare professionals.
How to handle: Develop clear scientific writing, data visualisation, presentations, and interdisciplinary communication skills.
See your match score
Register free to take the career quiz and get a personalised match % for this career, including subject gaps and university options.
Key skills
Resources