Aktis Oncology
Overview
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. The company is seeking a
Scientist, Computational Biology . This role will report to the Senior Director, Translational Science. Responsibilities
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. 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. Collaborate across the R&D organization to investigate heterogeneous data sets and generate visualizations to inform mechanism of action (MoA), biomarker discovery, and clinical development. Qualifications
Ph.D. in computational biology, bioinformatics, cancer biology, or related fields. 1–3 years of bioinformatics/computational biology research experience. Experience and Accomplishments
Demonstrated ability to develop internal tools, adopting and adapting publicly available data analysis tools and datasets to support R&D objectives. Experience building and implementing NGS analysis pipelines for large omics datasets (transcriptomics, genomics, proteomics, and others). Demonstrated success in developing and applying tools to integrate multi-omics data to elucidate mechanisms of response and resistance to targeted therapies. Strong technical background in handling, integrating, and analyzing large, diverse datasets, creating visualizations, and deriving insights (e.g., NGS, proteomics, PK/PD correlations). Required expertise includes:
Good understanding of cancer biology and/or immunology concepts. Experience with RNA-seq and genomic analysis pipelines from raw sequencing data to processed data (QC, trimming, mapping), differential gene expression (DEGs), gene ontology and pathway analysis. Familiarity with two or more programming languages (R, Python, Java, C++, SQL, etc.). Hands-on experience extracting and leveraging omics data from public data sources (e.g., GEO, MSigDB, cBioPortal, GTEx, DepMap, Human Metabolome, and others). Experience with generative AI and AI/ML libraries for bioinformatics applications (e.g., PyTorch, Pandas) for biomarker discovery and structure modeling; LLM experience is a plus.
Preferred expertise includes:
Single-cell sequencing, TCR sequencing, and/or immune transcriptomics knowledge. Experience in cloud computing and securely storing, maintaining, and backing up large datasets.
Equal Opportunity
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 applicable 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.
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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. The company is seeking a
Scientist, Computational Biology . This role will report to the Senior Director, Translational Science. Responsibilities
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. 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. Collaborate across the R&D organization to investigate heterogeneous data sets and generate visualizations to inform mechanism of action (MoA), biomarker discovery, and clinical development. Qualifications
Ph.D. in computational biology, bioinformatics, cancer biology, or related fields. 1–3 years of bioinformatics/computational biology research experience. Experience and Accomplishments
Demonstrated ability to develop internal tools, adopting and adapting publicly available data analysis tools and datasets to support R&D objectives. Experience building and implementing NGS analysis pipelines for large omics datasets (transcriptomics, genomics, proteomics, and others). Demonstrated success in developing and applying tools to integrate multi-omics data to elucidate mechanisms of response and resistance to targeted therapies. Strong technical background in handling, integrating, and analyzing large, diverse datasets, creating visualizations, and deriving insights (e.g., NGS, proteomics, PK/PD correlations). Required expertise includes:
Good understanding of cancer biology and/or immunology concepts. Experience with RNA-seq and genomic analysis pipelines from raw sequencing data to processed data (QC, trimming, mapping), differential gene expression (DEGs), gene ontology and pathway analysis. Familiarity with two or more programming languages (R, Python, Java, C++, SQL, etc.). Hands-on experience extracting and leveraging omics data from public data sources (e.g., GEO, MSigDB, cBioPortal, GTEx, DepMap, Human Metabolome, and others). Experience with generative AI and AI/ML libraries for bioinformatics applications (e.g., PyTorch, Pandas) for biomarker discovery and structure modeling; LLM experience is a plus.
Preferred expertise includes:
Single-cell sequencing, TCR sequencing, and/or immune transcriptomics knowledge. Experience in cloud computing and securely storing, maintaining, and backing up large datasets.
Equal Opportunity
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 applicable 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.
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