COMPANY DECK
WHAT ARE WE LOOKING FOR
We’re building a new kind of drug company, one where aging is treatable, resilience is restorable, and the limits of lifespan are pushed by design.
Computational Biologist / Bioinformatics Scientist
We are seeking a talented Computational Biologist or Bioinformatics Scientist to advance our target discovery platform. In this role, you'll work with cutting-edge multi-omics data to identify promising therapeutic targets and accelerate drug discovery.
You'll be responsible for processing large-scale datasets from genetics, single-cell, and proteomics studies. Your work will involve building reliable analysis pipelines, implementing SOTA methods, and developing production-ready code. The ideal candidate combines strong computational skills with a passion for translating complex biological data into actionable insights for drug development.
To apply please send your CV (indicate the title of the job post in the subject of an e-mail).
Send CV- Data management & preprocessing: tabular data, genetics data (plink format), GWAS sumstats, xQTL, RNA-Seq (bulk, single-cell), proteomics.
- Association Analysis: WGS and WES common and rare variants associations, statistical inference, classical ML.
- Post-GWAS integration & validation: genetic colocalization, mendelian randomization, transcriptomics and proteomics integration.
- Pipeline development & maintenance: design, build, and maintain automated analysis pipelines for association studies, ensure code quality.
- Education: BSc/MSc/PhD in Computational Biology, Bioinformatics, Biostatistics, Computer Science, Genetics, or related quantitative field.
- Minimum of 3+ years (BSc) or 1+ years (MSc) of relevant experience (or relevant doctoral research for PhD).
- Demonstrated hands-on experience analyzing large-scale omics datasets (GWAS, RNA-seq, proteomics, or other omics data).
- Advances Proficiency in Python: pandas/polars/spark, matplotlib+seaborn, scipy, scikit-learn, statsmodels.
- Intermediate R proficiency: ability to implement methods from research papers and modify existing code.
- Proficient in a Unix/Linux command-line environment.
- Practical experience with genetics and GWAS data preprocessing and analysis (plink, normalization, harmonization).
- Experience with implementing post-GWAS methods (e.g. finemapping, meta-analysis, etc.).
- Experience with workflow management systems (e.g., Nextflow, Snakemake, CWL) is highly desirable.
- Familiarity with bulk RNA-Seq and/or scRNA-Seq principles.
- Strong problem-solving skills and analytical thinking to address complex biological questions.
- Ability to work both independently and collaboratively in a fast-paced research environment.
- Proactive approach to learning new technologies and methodologies as the field evolves.
Medicinal Chemist – Small Molecule Drug Discovery
We are seeking a highly motivated Medicinal Chemist to join our small-molecule discovery team. The successful candidate will play a key role in designing, evaluating, and optimizing novel drug candidates. You will integrate structure-based drug design approaches (docking, FEP, molecular dynamics) with medicinal chemistry expertise to improve potency, selectivity, and physicochemical properties of our lead compounds.
To apply please send your CV (indicate the title of the job post in the subject of an e-mail).
Send CV- Design and optimize small molecules guided by structure-based drug design (SBDD), docking, and FEP simulations.
- Apply medicinal chemistry principles to optimize potency, selectivity, ADME, and physicochemical properties.
- Analyze SAR (structure–activity relationship) data and propose next-generation analogs.
- Collaborate with computational chemists, biologists, and DMPK scientists to advance drug discovery projects.
- Contribute to project strategy, compound design cycles, and hit-to-lead / lead optimization campaigns.
- Proven experience in small-molecule drug discovery and medicinal chemistry.
- Prior experience in a biotech or pharmaceutical drug discovery setting.
- Track record of contributing to hit-to-lead and lead optimization campaigns.
- Creativity in proposing next-generation analogs and problem-solving in challenging optimization projects.
- Strong ability to collaborate across disciplines, including computational chemistry, biology, and DMPK.
- Excellent written and verbal communication skills, including the ability to present research findings and strategic insights.
- Experience contributing to project strategy and design cycles within a multidisciplinary environment.
There are no open positions currently
If you think you could be a good fit for the team, please email the Careers team using the link below.
Send CV
