Job Description

Aktis Oncology is a biotechnology company pioneering the discovery and development of a new class of targeted alpha radiopharmaceuticals to treat a broad range of solid tumor cancers. Founded and incubated by MPM Capital, the company has developed proprietary platforms to generate tumor-targeting agents with ideal properties for alpha radiotherapy. Designed for high tumor penetration and long residence time, Aktis Oncology’s molecules will quickly clear other areas of the body, thereby maximizing tumor elimination while minimizing side effects of treatment. This approach would enable clinicians to visualize and verify target engagement prior to exposure to therapeutic radioisotopes.

Aktis Oncology is seeking a Scientist, Computational Biology. This role will report to the Senior Director, Translational Science.

DESCRIPTION

The Computational Biologist in the Translational Science group will work cross-functionally to support cancer biology initiatives across the Aktis portfolio and the advancement of novel programs from discovery to clinical development. She/he will independently apply and develop cutting-edge tools and methodologies to enable the analysis and interpretation of large multidimensional datasets in support of the company’s objectives. The translational/computational biology team member will work across the R&D organization, investigating heterogeneous data sets and generating visualizations to inform MoA, biomarker discovery, and clinical development.

BACKGROUND/TRAINING

• Ph.D. in computational biology, bioinformatics, cancer biology, or related fields.
• 1-3 years of bioinformatics/computational biology research experience.

EXPERIENCE/ACCOMPLISHMENTS

• Demonstrated ability to develop internal tools, adopting and adapting publicly available data analysis tools and datasets to support R&D Company objectives.
• Experienced in building and implementing NGS analysis pipelines to large sets of omics data, such as transcriptomics, genomics, proteomics and others.
• Demonstrated success in developing and applying tools to integrate multi-omics-based data sets to elucidate mechanisms of response and resistance to targeted therapies.
• Strong technical background in handling, integrating and analyzing large sets of diverse data creating visualizations, and deriving insights (i.e., NGS, proteomics, PK/PD correlations).
• Demonstrated ability to derive scientific insights from complex data sets, break down problems into simple components and effectively share findings with cross-functional colleagues.
• Effectively communicate and collaborate with other R&D team members, DMPK and clinical development teams to enable the adoption of data insights into drug development pipelines.
• Demonstrated high standards for scientific rigor, critical thinking, and building a culture of innovation that is fully aligned with company objectives
• Excels in team working environments, as a highly collaborative, positive and proactive individual.
• Thrives in fast-paced, flexible growth environments with the ability to work independently and in cross-functional teams.
• Excellent time management, organizational and communication skills.

Required expertise includes:

• Good understanding of cancer biology and/or immunology concepts.
• Experience with RNAseq and genomic analysis pipelines from raw sequencing data to processed data (data QC, trimming, mapping), differential gene expression (DEGs), gene ontology analysis and pathway analysis.
• Familiarity with two or more coding languages (R, python, java, C++, SQL…)
• Hands-on experience extracting and leveraging omics data from public data sources such as GEO, MSigDB, cBioportal, GTEX, Depmap, Human Metabolome, and others.
• Experienced with generative AI, AI/ML libraries for ML and data visualization applications to bioinformatics (i.e. pytorch, pandas…) (biomarker discovery, structure modelling…); LLMs is a plus.

Preferred expertise includes:

• Single-cell sequencing, TCR sequencing and/or immune transcriptomic knowledge is a plus.
• Experience in cloud computing and securely storing, maintaining and backing up large datasets.

Aktis Oncology is an Equal Opportunity Employer and does not discriminate on the basis of race, religion, color, sex, gender identity or expression, sexual orientation, age, disability, national origin, veteran status, or any other basis covered by appropriate law. Aktis Oncology is committed to promoting and maintaining a work environment in which all applicants, employees, and other individuals are treated with dignity and respect free from unlawful harassment, discrimination, or retaliation.