The Division of Compu­ta­tional and Molecular Prevention of the DKFZ, in colla­bo­ration with the Trans­la­tional Molecular Imaging in Oncologic Therapy Monitoring Unit, invites appli­ca­tions for a postdoc­toral researcher to join an inter­di­sci­plinary research program within the PRELUNG study, focusing on early lung cancer detection and biolo­gical charac­te­rization of pulmonary nodules.
This position combines cutting-edge multi­modal data analysis with patient-centered trans­la­tional research, including a novel co-design initiative on the return of molecular and imaging data to study parti­ci­pants.

Project Background:
Pulmonary nodules from hundreds of patients are being collected and biopsied as part of a prospective imaging study. Up to 40 FFPE biopsy samples will be analyzed using spatial transcrip­tomics and mutREAD DNA sequencing, enabling integrative analysis of spatial gene expression, tissue archi­tecture, and genomic altera­tions at early stages of lung carci­no­ge­nesis. The postdoc­toral researcher will play a central integrative role, leading unbiased compu­ta­tional analyzes, biolo­gical inter­pre­tation, and biomarker discovery in close colla­bo­ration with clini­cians, patho­lo­gists, and technology experts across multiple research groups.

Scien­tific & Compu­ta­tional Respon­si­bi­lities:

• Lead unbiased, data-driven integration of:
  • Spatial transcrip­tomics data
  • Genomic alteration profiles (copy number altera­tions, SNVs)
  • Histopa­tho­lo­gical diagnoses and clinical metadata
  • Radiomic features (in colla­bo­ration with imaging specia­lists)
• Perform unsuper­vised clustering and pattern discovery without prede­fined diagnostic labels
• Interpret molecular and microen­vi­ron­mental states of benign, prema­li­gnant, and malignant pulmonary nodules
• Identify and prioritize biomarkers for:
  • Liquid biopsy develo­pment
  • PET tracer target discovery
• Contribute to validation strategies (e.g. immun­o­hi­s­to­che­mistry) in colla­bo­ration with patho­lo­gists
• Lead the prepa­ration of high-impact, inter­di­sci­plinary publi­ca­tions

Trans­la­tional & Colla­bo­rative Respon­si­bi­lities:

• Act as a scien­tific integrator across multiple colla­bo­rating research groups
• Commu­nicate effec­tively with clini­cians, patho­lo­gists, imaging scien­tists, and molecular techno­lo­gists
• Maintain repro­du­cible and well-documented analysis workflows

Patient Engagement & Return-of-Data Work Package:

• Actively parti­cipate in a parti­cipant-driven co-design process to develop a framework for returning molecular and imaging data to study parti­ci­pants
• Contribute scien­tific content to patient workshops and plain-language commu­ni­cation materials
• Co-facilitate workshops together with ethicists, commu­ni­cation experts, and insti­tu­tional partners
• Help synthesize parti­cipant feedback into struc­tured outputs, including:
  • A return-of-data blueprint
  • Prototype parti­cipant reports
  • An evaluated framework for future imple­men­tation

YOUR PROFILE

• PhD in compu­ta­tional biology, bioin­for­matics, systems biology, biome­dical data science, cancer biology, or a related field
• Strong experience in omics data analysis, ideally including single-cell or spatial transcrip­tomics
• Profi­ciency in R and/or Python and modern data-analysis workflows
• Experience with unsuper­vised learning, clustering, and integrative analysis
• Ability to translate compu­ta­tional findings into meaningful biolo­gical and trans­la­tional insights
• Strong interest in early cancer detection and biomarker discovery
• Excep­tional inter­per­sonal and commu­ni­cation skills
  • Excellent commu­ni­cation skills across diverse audiences (patients, clini­cians, compu­ta­tional scien­tists)
  • Empathy, active listening, and comfort engaging with non-expert stake­holders
  • Ability to discuss uncer­tainty and non-actionable findings respon­sibly
  • Confi­dence contri­buting to group facili­tation without reliance on hierar­chical authority
  • A colla­bo­rative, inclusive, and respectful working style

Appli­cants are encou­raged to highlight concrete evidence of these skills (e.g. patient-facing research, public engagement, teaching, facili­tation, or inter­di­sci­plinary leadership).

You can look forwad to: 

• Active invol­vement in innovative patient-centered research initia­tives
• Close inter­action with clini­cians, patho­lo­gists, and technology developers
• Oppor­tunity to lead high-impact publi­ca­tions

Appli­cation: 

Interested appli­cants should submit the following documents via our online appli­cation tool:

• A cover letter describing your scien­tific interests and motivation for this inter­di­sci­plinary and patient-engaged role
• Curri­culum vitae
• Contact details of 2–3 references

Apply at: https://jobs.dkfz.de/en/jobs/168576/postdoctoral-researcher-computational-translational-analysis-of-pulmonary-nodules