265 Senior Research Scientist Molecular Biology jobs in Nairobi

• Design, conduct, and optimize advanced molecular biology experiments.
• Develop and validate novel molecular techniques and assays.
• Analyze and interpret complex biological data, including genomic and proteomic information.
• Troubleshoot experimental challenges and identify effective solutions.
• Contribute to the development of new research strategies and project proposals.
• Collaborate with interdisciplinary research teams to achieve project objectives.
• Prepare manuscripts for publication in peer-reviewed journals.
• Present research findings at scientific conferences and internal meetings.
• Mentor and guide junior research staff.
• Stay current with scientific literature and emerging trends in molecular biology.

• Ph.D. in Molecular Biology, Biochemistry, Genetics, or a related life science discipline.
• Minimum of 5 years of post-doctoral research experience in a relevant field.
• Demonstrated expertise in molecular biology techniques (e.g., PCR, qPCR, Western Blotting, CRISPR, Next-Generation Sequencing).
• Proven experience in experimental design, data analysis, and interpretation.
• Strong publication record in reputable scientific journals.
• Proficiency in bioinformatics tools and data analysis software is highly desirable.
• Excellent problem-solving, critical thinking, and analytical skills.
• Exceptional written and verbal communication skills.
• Ability to work independently and collaboratively in a remote research setting.
• Strong understanding of laboratory safety protocols and ethical research practices.

• Lead and mentor a team of postdoctoral fellows, research assistants, and technicians in a remote setting.
• Design, develop, and implement cutting-edge research projects in areas such as oncology, infectious diseases, or neurobiology.
• Oversee experimental design, data collection, and rigorous data analysis.
• Secure research funding through competitive grant applications and collaborations.
• Publish research findings in high-impact, peer-reviewed scientific journals.
• Present research outcomes at international scientific conferences and internal meetings.
• Collaborate with internal and external collaborators, including industry partners, to advance research objectives.
• Ensure compliance with all laboratory safety protocols, ethical guidelines, and regulatory requirements.
• Manage research budgets, equipment, and resources effectively.
• Stay abreast of the latest scientific advancements and methodologies in the relevant field.

A Business Data Analytics and Research intern plays a crucial role in organizations by leveraging data to drive strategic decision-making, conducting research to identify market trends, and optimizing business operations. Below are key responsibilities and skills typically associated with this role:

Key Responsibilities:

1. Data Collection and Analysis
   :

2. Gather and analyze business, market, and financial data from various sources to provide insights into performance and trends.

3. Use statistical tools to interpret data sets, identifying patterns and trends that inform business decisions.

2.Data Visualization, Reporting and Presentation
:

• Prepare and present detailed reports, dashboards, and visualizations that summarize key data insights and findings.
• Communicate complex data results to non-technical stakeholders in a clear and actionable manner.
• Capacity to develop concept notes and proposals based on market research gaps

3. Market Research
:

• Conduct qualitative and quantitative research to identify new market opportunities, competitor analysis, and customer preferences.
• Evaluate market conditions, industry trends, and competitors' activities to support business growth strategies.
• Prepare presentations based on market research reports

4.Business Performance Monitoring
:

• Monitor key performance indicators (KPIs) to track business progress and identify areas for improvement.
• Recommend improvements based on data insights to optimize processes, reduce costs, and increase profitability.

5.Collaborating with Teams
:

• Work closely with different departments such as marketing, finance, and operations to align data-driven insights with business objectives.
• Provide support for product development, sales strategies, and customer experience initiatives through data analysis.

6.Data Management
:

• Ensure the accuracy, completeness, and security of data.
• Develop and maintain databases, data collection systems, and strategies for efficient data storage and retrieval.

Key Skills:

1.Data Analytics Tools
:

• Proficient in tools like SQL, Excel, Tableau, Power BI, Google Analytics, and other business intelligence platforms.

2.Statistical Analysis
:

• Knowledge of statistical software (e.g., R, SAS, SPSS) and techniques such as regression analysis, hypothesis testing, and predictive modeling.

3.Research and Excellent Writing skills:

• Strong ability to conduct both primary and secondary research, including surveys, interviews, and literature reviews.
• Capacity to develop report and concepts based on market research reports

4.Problem-Solving
:

• Analytical thinking to identify issues, trends, and opportunities through data, and propose actionable solutions.

5.Communication Skills
:

• Excellent written and verbal communication skills to present findings and recommendations clearly to stakeholders.

6.Attention to Detail
:

• High level of precision in handling large data sets and ensuring data accuracy.

7.Project Management
:

• Ability to manage multiple research projects simultaneously, ensuring timely delivery of results.

Education, knowledge and experience:

• A degree in Agricultural Economics or a related field.
• Experience in management and analysis of data.
• Field experience and synthesis of data and lessons for learning
• Knowledge and savvy of data analysis software, especially Stata.
• Very strong analytical skills and applied statistical experience.
• Good scientific wring experience.

• Analyze diverse biological datasets, including genomics, transcriptomics, proteomics, and metabolomics data.
• Develop, implement, and validate bioinformatics pipelines and algorithms for data analysis.
• Utilize statistical methods and machine learning techniques to identify patterns and derive biological insights.
• Collaborate closely with experimental scientists to design studies, interpret results, and contribute to manuscript preparation.
• Contribute to the development of new research hypotheses and experimental strategies.
• Manage and organize large biological datasets, ensuring data integrity and reproducibility.
• Develop custom scripts and software tools to support research needs.
• Stay current with the latest advancements in bioinformatics, computational biology, and relevant biological fields.
• Present research findings at scientific meetings and contribute to publications in peer-reviewed journals.
• Participate in grant writing efforts to secure funding for research projects.

• Ph.D. in Bioinformatics, Computational Biology, Computer Science, Statistics, or a related quantitative field.
• Minimum of 4-6 years of relevant research experience in bioinformatics or computational biology.
• Proficiency in programming languages such as Python and R, with experience in relevant libraries (e.g., Biopython, NumPy, SciPy, ggplot2).
• Experience with next-generation sequencing (NGS) data analysis.
• Solid understanding of statistical methods and machine learning algorithms.
• Familiarity with Unix/Linux operating systems and command-line tools.
• Experience with database management and query languages (e.g., SQL).
• Strong analytical and problem-solving skills.
• Excellent written and verbal communication skills, with the ability to explain complex technical concepts to diverse audiences.
• Ability to work independently and collaboratively in a remote team environment.

• Design, direct, and execute novel research projects in genomics and related fields.
• Develop and optimize advanced genomic analysis pipelines and methodologies.
• Analyze and interpret large-scale genomic datasets (e.g., whole-genome sequencing, RNA-Seq, epigenomics) using bioinformatics tools and statistical modeling.
• Collaborate with interdisciplinary teams of scientists, bioinformaticians, and statisticians to advance research objectives.
• Prepare and present research findings at international conferences and publish in peer-reviewed journals.
• Secure external funding through grant writing and proposal development.
• Mentor and supervise junior scientists and research staff.
• Contribute to the strategic direction of the research division and identify new areas of scientific inquiry.
• Maintain meticulous laboratory notebooks and research records in a digital format.
• Stay abreast of the latest advancements in genomics, bioinformatics, and related scientific disciplines.
• Participate in virtual journal clubs, seminars, and collaborative working groups.

• Ph.D. in Genetics, Molecular Biology, Bioinformatics, or a closely related field.
• Minimum of 10 years of post-doctoral research experience in genomics.
• Demonstrated track record of leading independent research projects and securing funding.
• Extensive experience with various next-generation sequencing (NGS) technologies and platforms.
• Proficiency in programming languages relevant to bioinformatics (e.g., Python, R, Perl) and statistical analysis.
• Expertise in using bioinformatics tools and databases for genomic data analysis.
• Strong publication record in high-impact, peer-reviewed journals.
• Excellent written and verbal communication skills for remote collaboration and scientific dissemination.
• Proven ability to mentor and lead research teams effectively.
• Experience with computational biology and machine learning applied to biological data is highly advantageous.
• Ability to work autonomously and manage multiple research projects concurrently in a remote setting.

• Lead and conduct advanced bioinformatics research projects.
• Develop and apply computational methods for biological data analysis.
• Manage and analyze large genomic, transcriptomic, and proteomic datasets.
• Collaborate with biologists and other researchers to interpret findings.
• Mentor junior scientists and contribute to team development.
• Author research papers and present findings at conferences.
• Contribute to grant writing and funding applications.

• Ph.D. in Bioinformatics, Computational Biology, or a related field.
• Proven experience in leading research projects.
• Expertise in programming (Python, R) and statistical analysis.
• Strong knowledge of machine learning and data mining techniques.
• Experience with high-throughput sequencing data analysis.
• Excellent scientific writing and presentation skills.
• Demonstrated ability to work independently and collaboratively in a remote setting.