Ref. 59-2023 Bioinformatician for the Biomarkers and Clonal Dynamics Group

The Vall d´Hebron Institute of Oncology (VHIO) Seeks a “Bioinformatician for the Biomarkers and Clonal Dynamics Group”

Reference: Ref. 59-2023

Application deadline: until position filled

Number of vacancies: 1

Job description:
The Vall d'Hebron Institute of Oncology (VHIO) in Barcelona is seeking an exceptional bioinformatician to join the VHIO-IMMUNOMICs project. Over the past 5 years, the project has collected and processed longitudinal tumor and plasma samples from pan-cancer patients undergoing immunotherapy. The VHIO-IMMUNOMICs project is a European-funded translational initiative resulting from the collaboration between Dr. Rodrigo Toledo's Biomarkers and Clonal Dynamics Group and Dr. Elena Garralda's Early Drug Development Group and Phase I Unit – UITM.

Our Goals:
1. Identify mechanisms of sensitivity and resistance to immune checkpoint inhibitors.
2. Characterize the prognostic and predictive value, as well as the evolutionary dynamics, of plasma ctDNA in the context of cancer immunotherapy.
3. Discover new potential therapeutic targets that can reduce resistance and enhance the efficacy of cancer immunotherapy.

Our Approach:
To generate and analyze multi-omics data (WGS, WES, RNAseq) from tumor and plasma cell-free DNA samples collected before, during, and at progression to immunotherapy. These results will be correlated with clinical data and outcomes.

This position is ideal for candidates who enjoy challenges, learning new concepts, and possess excellent communication skills.

- Bachelor's degree in bioinformatics or postgraduate studies in bioinformatics, computational biology, or a related field.
- Minimum of 2 years of experience in Omics projects.
- Proficiency in processing and analyzing WES, WGS, RNA-seq, and other relevant datasets.
- Fluency in R, Python, and Bash (GNU/Linux) scripting. Knowledge of other programming languages will be advantageous.
- Experience in version control programming (e.g., Git) and hosting (e.g., GitHub).
- Familiarity with high-performance computing environments (e.g., Slurm).
- Experience with container systems (e.g., Docker or Singularity) is a plus.
- Familiarity with Nextflow or similar workflow managers is a plus.
- Experience with Amazon AWS or similar cloud providers is a plus.
- Knowledge of statistical modeling, machine learning, and deep learning is a plus.

The candidate is expected to have excellent oral and written communication skills in English.
Salary will be commensurate with experience and profile and according to our Collective Agreement pay scale.

Interested applicants should email their comprehensive Curriculum Vitae and a Cover Letter to

About VHIO:
Under the leadership of Josep Tabernero, the Vall d’Hebron Institute of Oncology (VHIO), has established itself as a comprehensive cancer center of proven excellence internationally. It is also thanks to VHIO’s optimal organizational structure based on a purely multidisciplinary and translational model that VHIO talents continue to anticipate and tackle the many unresolved questions in combatting this multifaceted and heterogeneous disease.
Located within the Vall d’Hebron Barcelona Hospital Campus, our researchers closely collaborate and interact with Vall d’Hebron physician-scientists. Translational science and clinical research are therefore tightly connected which promotes superb interaction and teamwork which, in turn, accelerates the bench-bedside-bed cycle of knowledge. This privileged environment affords VHIO direct access to patients as well as the entire spectrum of oncology professionals who care for them, and a second-to-none appreciation of how cancer science can translate into more powerful, targeted treatments and better practice for the care of patients.
VHIO’s pioneering model and programs, coupled with its belief in combining strengths through cross-border collaborations, continue to spur advances in reversing cancer resistance, halting metastatic spread, and more effectively treating even the most undruggable tumor types.

VHIO’s translation toward precision oncology: