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Veröf­fent­licht: 2. June 2026

Postdoc­toral Researcher (f/m/d, E13 TV‑L, 100%)

Prof. Dr. Nico Pfeifer’s Chair for Methods in Medical Infor­matics, Department of Computer Science at the University of Tübingen, distin­gu­ished as excellent by the Federal Government of Germany, is inviting appli­ca­tions for a

3‑year Postdoc­toral Researcher Position
(f/m/d, E13 TV‑L, 100%)

Please find more infor­mation on https://uni-tuebingen.de/en/university/careers/newsfullview-job-advertisements/article/postdoctoral-researcher-f-m-d-e13-tv-l-100/

Veröf­fent­licht: 1. June 2026

Postdoc­toral Researcher (f/m/d) in Medical Bioin­for­matics (University Medical Center Göttingen)

We are seeking a

Postdoc­toral Researcher (f/m/d)

Full-time (100%)  TV‑L  ·  initially 2 years (with option of extension)

 

About Us

The Department of Medical Bioin­for­matics at the University Medical Center Göttingen is a leading research group in the bioin­for­matic analysis of biome­dical high-throughput data. Our work focuses on the develo­pment of biomarker signa­tures, statis­tical methods, and machine learning approaches for perso­na­lised and systems medicine.

We are embedded in multiple DFG- and BMBF-funded colla­bo­rative research projects, with a strong focus on the analysis of cancer omics data — including genomics, transcrip­tomics, and spatial transcrip­tomics — and the develo­pment of innovative AI and machine learning methods. We work in close colla­bo­ration with clinical and experi­mental partners in national and inter­na­tional research consortia.

 

Your Tasks

  • Analysis and integration of cancer multi-omics datasets (transcrip­tomics, epige­nomics, drug-response data)
  • Develo­pment of machine learning and AI models for biomarker discovery and prediction of treatment response
  • Appli­cation and further develo­pment of graph-based learning methods enriched with biolo­gical pathway and drug–target knowledge
  • Bench­marking of novel models against existing compu­ta­tional approaches
  • Inter­pre­tation of results in close colla­bo­ration with clinical and experi­mental consortium partners
  • Independent management of bioin­for­matics sub-projects and contri­bution to project coordi­nation
  • Prepa­ration and submission of scien­tific manuscripts and reports

 

Your Profile

  • PhD in Bioin­for­matics, Compu­ta­tional Biology, Computer Science, or a closely related field
  • Proven experience in machine learning or deep learning applied to biome­dical data
  • Strong programming skills in Python, R, or similar languages
  • Expertise in the analysis of large-scale omics datasets (e.g. transcrip­tomics, methy­lomics, drug-response data)
  • Experience with graph-based methods or network biology is an advantage
  • Track record of scien­tific publi­ca­tions appro­priate to career stage
  • Ability to work independently and lead projects, while colla­bo­rating effec­tively in an inter­di­sci­plinary team
  • Excellent written and spoken English; knowledge of German is advan­ta­geous

 

What We Offer

  • A leading research environment at the inter­section of AI, multi-omics, and trans­la­tional cancer medicine
  • Colla­bo­ration with national and inter­na­tional clinical and experi­mental partners
  • Access to large-scale biome­dical datasets and state-of-the-art computing infra­structure
  • Salary according to TV‑L (full-time, 100%) for an initial period of 3 years, with the possi­bility of extension
  • Additional occupa­tional pension scheme (VBL)
  • Company health management programme and sports facilities
  • Support for career develo­pment, confe­rence atten­dance, and inter­na­tional networking
  • A position in Göttingen — a vibrant university city with a rich scien­tific tradition

 

Diversity & Inclusion

The University Medical Center Göttingen is committed to profes­sional equality for all genders and actively works to achieve gender balance across all areas. We warmly welcome appli­ca­tions from severely disabled persons, who will be given prefe­rential conside­ration in the case of equal suita­bility in accordance with appli­cable regula­tions. Please indicate any disability or relevant status in your appli­cation to ensure your interests are protected.

 

How to Apply

Please submit your appli­cation (CV, cover letter, and relevant certi­fi­cates) by 12.06.026via the following link:

https://umg.recruiting-portal.com/r/z10iypob1b9umbp/Postdoctoral+Researcher+fmd/37075/G%C3%B6ttingen

 

Please note that travel and appli­cation costs cannot be reimbursed.

We look forward to receiving your appli­cation!

 

Veröf­fent­licht: 1. June 2026

PhD Student (f/m/d) in Medical Bioin­for­matics (University Medical Center Göttingen)

We are seeking a

PhD Student (f/m/d)

Part-time (65%)  ·  TV‑L  ·  2 years (with option of extension)

 

About Us

 

The Department of Medical Bioin­for­matics at the University Medical Center Göttingen is a leading research group in the bioin­for­matic analysis of biome­dical high-throughput data. Our work focuses on the develo­pment of biomarker signa­tures, statis­tical methods, and machine learning approaches for perso­na­lised and systems medicine.

We are embedded in multiple DFG- and BMBF-funded colla­bo­rative research projects, with a strong focus on the analysis of cancer omics data — including genomics, transcrip­tomics, and spatial transcrip­tomics — and the develo­pment of innovative AI and machine learning methods. We work in close colla­bo­ration with clinical and experi­mental partners in national and inter­na­tional research consortia.

Within these research groups, we offer ambitious young scien­tists the oppor­tunity to work at the forefront of research in Medical Bioin­for­matics. Possible topics for doctoral theses are deeply rooted in the analysis of complex datasets and the develo­pment of methods essential for progress in the treatmemt of cancer.

We are looking for PhD candi­dates interested in statis­tical data analysis, machine learning methods, gene regulation, bioin­for­matics, and integrative omics approaches.

 

 

Your Tasks

  • Analysis of cancer multi-omics data (transcrip­tomics, epige­nomics, metage­nomics)
  • Develo­pment and appli­cation of statis­tical and machine learning approaches for biomarker discovery
  • Integration of multi-omics datasets across patient cohorts
  • Processing and analysis of NGS-based datasets and bioin­for­matics pipelines
  • Contri­bution to the inter­pre­tation of results in close colla­bo­ration with clinical and experi­mental partners
  • Support in data and project management
  • Prepa­ration of scien­tific manuscripts and reports

 

Your Profile

  • Sc. or Diploma in Bioin­for­matics, Computer Science, Data Science, Biology, or a related field
  • Solid under­standing of biolo­gical and biome­dical concepts, parti­cu­larly in the context of cancer or genomics
  • Experience and strong interest in machine learning, statis­tical modelling, and data science
  • Profi­ciency in at least one programming language (Python, R, or similar)
  • Familiarity with NGS data analysis and bioin­for­matics workflows is an advantage
  • Enthu­siasm for working with large, complex, and hetero­ge­neous datasets
  • Interest in inter­di­sci­plinary research and colla­bo­ration across multiple insti­tu­tions
  • Excellent written and spoken English; knowledge of German is advan­ta­geous
  • High motivation, initiative, and the ability to work both independently and as part of a team

 

What We Offer

  • An exciting research environment at the interface of bioin­for­matics, AI, and cancer medicine
  • Struc­tured mentoring and a supported onboarding process
  • A diverse, inter­di­sci­plinary, and multi-profes­­­sional working environment
  • Access to state-of-the-art bioin­for­matics infra­structure and large-scale biome­dical datasets
  • Salary according to TV‑L (part-time, 65%) for an initial period of 3 years, with the possi­bility of extension
  • Additional occupa­tional pension scheme (VBL)
  • Company health management programme and sports facilities
  • A position in Göttingen — a vibrant university city with a rich scien­tific tradition

 

Diversity & Inclusion

The University Medical Center Göttingen is committed to profes­sional equality for all genders and actively works to achieve gender balance across all areas. We warmly welcome appli­ca­tions from severely disabled persons, who will be given prefe­rential conside­ration in the case of equal suita­bility in accordance with appli­cable regula­tions. Please indicate any disability or relevant status in your appli­cation to ensure your interests are protected.

 

How to Apply

Please submit your appli­cation (CV, cover letter, and relevant certi­fi­cates) by 12.06.2026 via the following link:

https://umg.recruiting-portal.com/r/z01r7ubt7k6t97q/PhD+Position+fmd/37077/G%C3%B6ttingen

 

Please note that travel and appli­cation costs cannot be reimbursed.

We look forward to receiving your appli­cation!

Veröf­fent­licht: 29. May 2026

Postdoc in Compu­ta­tional Biology: Leading the EpiFlaMe consortium

Postdoc in Compu­ta­tional Biology

Leading the EpiFlaMe consortium
(Memory in Epithelial Cells — Organ Speci­ficity and Cancer)

The group: The candidate will be part of the Compu­ta­tional Systems Biology group at the University of Salzburg, which is headed by Nikolaus Fortelny (https://plus.ac.at/fortelny). The group is focused on integrating single-cell/s­­­patial multi-omics data with biolo­gical knowledge using AI/ML and other compu­ta­tional approaches in cancer and immunology research. We focus on approaches that produce robust, reliable, and ideally inter­pr­e­table results.

The project: EpiFlaMe (Memory in Epithelial Cells — Organ Speci­ficity and Cancer: https://plus.ac.at/epiflame) is a large consortium of seven research groups dedicated to under­standing inflamm­atory memory in epithelia. The postdoc will be supported by a bioin­for­matics technician to coordinate and perform integrative bioin­for­matic data analysis of multi-omics profiles generated by these various groups, focusing on producing a consortium flag-ship publi­cation (similar to Fortelny et al., Nature Immunology, 2024). The project focuses on under­standing epithelial inflamm­atory memory and its relati­onship with cancer develo­pment. Using multi-omics profiling, innovative organoid cell cultures and in-vivo models the consortium will create the first syste­matic molecular map of inflamm­atory memory in epithelial cells across multiple organs. The goal of the EpiFlaMe research program is to lay the foundation for future therapies that can treat chronic inflamm­atory diseases and help prevent tumor formation in an organ-specific way.

The place: The city of Salzburg has ample natural and cultural attrac­tions as well as fast connec­tions to Vienna and Munich. It is surrounded by beautiful lakes and mountains, with various oppor­tu­nities for recrea­tional and sports activities. The university has 18 000 students, and a highly colla­bo­rative research environment in both biome­dical and compu­ta­tional sciences.

Quali­fi­ca­tions:
* PhD in biology, bioin­for­matics, biotech­nology, computer science, statistics, physics, or similar
* Excellent scien­tific thinking and commu­ni­cation, high level of motivation and drive
* Programming (R/python) and other quanti­tative skills (statistics, AI/ML, network biology)
* Experience with (multi-)omics integrative data analysis, single-cell / spatial data, and/or CRISPR screens
* An under­standing of and interest in immunology
* Excellent English and commu­ni­cation skills, especially commu­ni­cation with wet-lab biolo­gists

Details:
* Start date: as soon as possible
* Duration: end of 2029 (project may then be prolonged for 4 years)
* Salary and work hours according to Austrian funding regula­tions
* Place of work: Salzburg, Austria

Our offer:
* Experience in coordi­nating a large research consortium focused on how immunology drives cancer
* Cutting-edge academic environment (https://scholar.google.at/citations?user=IHjaqgkAAAAJ)
* Being part of an inter­na­tional, inter­di­sci­plinary, and fun team and consortium
* Oppor­tu­nities for self-growth through courses for hard and soft skills
* Parti­ci­pation in confe­rences and project meetings
* Excellent social benefits of working in Austria (holidays, health insurance)
* Environment that values a healthy work / life balance

Appli­cation:
https://survey.plus.ac.at/index.php/282137

Deadline:
None — we hire on a rolling basis.

We look forward to hearing from you!

Veröf­fent­licht: 20. May 2026

Postdoc­toral Researcher — Compu­ta­tional & Trans­la­tional Analysis of Pulmonary Nodules

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

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