Microbiologist Product Manager– MicroBoost AI

Evogene is looking for a Product Manager with a strong microbiology background to join the MicroBoost AI multidisciplinary product team. The candidate will lead the development of an innovative computational tool platform specifically aimed to support microbial products development for the Ag, Pharma, and Environmental industries.

As a microbiologist product manager, you will be responsible for leveraging computational techniques and bioinformatics tools to analyze complex biological data related to microorganisms. Your primary focus will be on understanding microbial diversity, evolution, genomics, and functional genomics. You will collaborate with microbiologists, geneticists, bioinformaticians, and end user scientists to interpret biological data and contribute to research projects aimed at advancing development of microbial products.

Additionally, you will be expected to stay abreast of developments in the fields of microbiology, computational biology, and bioinformatics, and apply emerging technologies and methodologies to product research and development.

Main responsibilities:

1. Analyze genomic, transcriptomic, metagenomic, and other -omics data to study microbial communities and their interactions.

2. Apply computational methods for microbial genome assembly, annotation, and comparative genomics.

3. Collaborate with experimental biologists to design experiments and interpret experimental results using computational approaches.

4. Contribute to the development of software tools and pipelines for processing and analyzing biological data.

5. Stay informed about the latest advancements in computational biology, bioinformatics, and microbiology research.

6. Work collaboratively within interdisciplinary teams to address complex scientific questions and achieve project goals.

Qualifications:

1. A Ph.D. or equivalent degree in microbiology, bioinformatics, computational biology, or a related field.

2. Strong analytical and problem-solving skills, with experience in analyzing large biological datasets.

3. Familiarity with bioinformatics tools and databases commonly used in microbiology research (e.g., NCBI, BLAST, NGS for metagenomic analyses etc.).

4. Experience with genomic analysis tools and techniques (e.g., genome assembly, gene prediction, comparative genomics, etc.).

5. Knowledge of statistical methods and machine learning techniques applied to biological data analysis.

6. Excellent communication skills, with the ability to present complex scientific concepts to both technical and non-technical audiences.

7. Ability to work effectively in a collaborative, interdisciplinary research environment.

8. Proven industrial experience in managing computational microbial product development is an advantage.