We seek a highly motivated Compu­ta­tional Scientist (m/f/d) for Cancer Antigen Discovery to join our Compu­ta­tional Genomics unit. We are an inter­di­sci­plinary team of scien­tists, PhD students, and software engineers passionate about developing bioin­for­matics tools to identify biomarkers and thera­peutic targets for perso­na­lized immuno­the­rapies against cancer. In close colla­bo­ration with other teams at TRON, as well as with partners from academia, clinics and industry, we apply our compu­ta­tional approaches to discover antigen targets and translate them into clinical practice.

The successful candidate will be respon­sible for identi­fying and priori­tizing novel classes of tumor-specific antigens for perso­na­lized mRNA vaccines and other immuno­the­rapies. This will be achieved through the analysis of multi-omics data, using innovative compu­ta­tional approaches supported by validation through molecular and immuno­lo­gical assays.

Your tasks and respon­si­bi­lities:

• Analyze large cohorts of genomic, epige­nomic, transcrip­tomic and proteomics data to identify and prioritize novel tumor-specific candidate antigens relevant for cancer immuno­the­rapies.
• Develop compu­ta­tional pipelines for antigen target detection in individual patients for perso­na­lized therapies.
• Contribute to the design of validation strategies and colla­borate on confirming targets through molecular and immuno­lo­gical assays.
• Present and discuss in internal meetings and inter­na­tional confe­rences, writing R&D reports and scien­tific publi­ca­tions.

What you bring:

• D. in Compu­ta­tional Biology, Immuno-Oncology, or a related data-driven field with at least 2 years of postdoc­toral research experience in academia or industry.
• Demons­trated scien­tific expertise in tumor immunology and target discovery for immuno­the­rapies.
• Excellent programming skills for repro­du­cible data analysis in Python or R.
• Experience analyzing next-generation sequencing (NGS) data. Experience with mass spectro­­­metry-based immun­o­pep­ti­domics data analysis is a plus.
• Hands-on expertise with version control systems (e.g., Git), workflow managers (e.g., Nextflow or Snakemake), and high-perfor­­­mance computing environ­ments.
• Experience leading research projects in a multi­di­sci­plinary environment and comfor­table working in a dynamic and evolving environment.

Enthu­siasm and curiosity for the diverse activities of our research institute completes your profile.

We offer:

• A dynamic, innovative, and creative research environment with strong expertise in immuno­the­rapies.
• An open, collegial, and supportive working atmosphere in a respectful organiza­tional culture
• A highly diverse and inclusive workforce
• Access to our GPU-accele­rated HPC cluster and labora­tories with cutting-edge sequencing techno­logies and molecular assays.
• Perfor­­­mance-based remune­ration and other benefits
• Oppor­tu­nities for perso­na­lized profes­sional develo­pment
• Conve­nient access via public transport and car as well as bicycle parking spaces
• The possi­bility of hybrid working arran­ge­ments

TRON is an inter­na­tio­nally recog­nised institute for appli­­­­­cation-oriented research. We combine the strengths of academic research with the requi­re­ments of quality-controlled indus­trial develo­p­ments. At TRON, we share a common mission to develop innovative solutions for the immuno­the­ra­peutic treatment of cancer, infec­tious diseases and other serious diseases with high medicinal need for develo­pment.

TRON was founded in Mainz in 2010 and works in close coope­ration with univer­sities and hospitals as well as with regional, national and inter­na­tional research insti­tu­tions and pharmaceu­tical companies.

As part of our team, you have the oppor­tunity to be at the forefront of trans­la­tional science with us.

If all this appeals to you, we look forward to getting to know you.

Please send us your complete and infor­mative appli­cation documents (cover letter, CV, references) in a single document of max. 5 MB by e‑mail to Human Resources at jobs (at) tron-mainz.de,
Job-ID: 43104–25–02-WAPRO.

For more infor­mation, visit our homepage at www.tron-mainz.de

The Technical University of Munich (TUM) invites appli­ca­tions for the position of

Professor

in »Machine Learning

for Sustainable Processes and Materials«

W3 Associate Professor; to begin as soon as possible.

Scien­tific environment

The profes­sorship will be assigned to the TUM Campus Straubing for Biotech­nology and Sustaina­bility and will play a central role in inter­di­sci­plinary and trans­di­sci­plinary research at the interface between data science, life sciences, and bioeco­nomics. The professor will closely cooperate with the TUM School of Compu­tation, Infor­mation and Technology (CIT), the TUM School of Life Sciences (LS), and with the Excel­lence Cluster BioSysteM.

Respon­si­bi­lities

The respon­si­bi­lities include research and teaching as well as the promotion of early-career scien­tists. We seek to appoint an expert in the research area of Machine Learning for Sustainable Processes and Materials with a focus on data-driven methods for modeling, analyzing, and optimizing complex biolo­gical, biotech­no­lo­gical and agricul­tural systems. The main focus is on machine learning approaches, in parti­cular statis­tical learning, reinforcement learning, deep learning, and computer vision, as well as the statis­tical and bioin­for­matics analysis of chemical and biolo­gical processes and systems, and to gain a deeper under­standing of bioche­mical and biotech­no­lo­gical processes and systems through the integration of modern data science, machine learning and bioin­for­matics methods. This also includes modern in silico methods for analyzing genomic, genetic, and pheno­typic data. The focus is on applying data science methods to support the transition to a sustainable bioeconomy, taking into account economic and social science aspects. Teaching respon­si­bi­lities include courses in the university’s bachelor and master programs at TUMCS (Profes­sional Profile Bioeconomy) in German and English.

Quali­fi­ca­tions

We are looking for candi­dates who have demons­trated excellent achie­ve­ments in research and teaching in an inter­na­tio­nally recognized scien­tific environment, relative to the relevant career level (please see www.tum.de/en/faculty-recruiting-faq/ for further infor­mation).

A university degree in bioin­for­matics and an outstanding doctoral degree or equivalent scien­tific quali­fi­cation, as well as pedago­gical aptitude, are prere­qui­sites. Substantial research experience abroad is expected. Successful appli­cants will have the proven ability to acquire and to lead coope­rative research projects and to attracting third-party funding.

Our Offer

Based on the best inter­na­tional standards and trans­parent perfor­mance criteria, TUM offers a merit-based academic career through a permanent position as Associate Professor, and on to Full Professor. The regula­tions of the TUM Faculty Recruitment and Career System apply.

TUM provides excellent working condi­tions in a lively scien­tific community, embedded in the vibrant research environment of the Greater Munich Area and in Straubing. The TUM environment is multi­cul­tural, with English serving as a common interface for scien­tific inter­action. TUM offers attractive and perfor­­­mance-based salary condi­tions and social benefits.

The TUM Munich Dual Career Office (MDCO) provides tailored career consulting to the partners of newly appointed professors. The MDCO assists the relocation and integration of new professors, their partners and accom­panying family members.

Your Appli­cation

TUM is an equal oppor­tunity employer and expli­citly encou­rages appli­ca­tions from women. The position is suitable for disabled persons. Disabled appli­cants will be given prefe­rence in case of generally equivalent suita­bility, aptitude and profes­sional perfor­mance. Appli­cation documents should be submitted in accordance with TUM’s appli­cation guide­lines for professors. These guide­lines and detailed infor­mation about the TUM Faculty Recruitment and Career System are available at www.tum.de/faculty-recruiting. Here you will also find TUM’s infor­mation on collecting and processing personal data as part of the appli­cation process.

Please submit your appli­cation by 30 September 2025 via the TUM recruitment portal: www.recruit.tum.de.

We are seeking a motivated Bioin­for­matics Software Developer (m/f/d) to join our Compu­ta­tional Genomics unit. We are an inter­di­sci­plinary team of scien­tists, PhD students, and software engineers who develop bioin­for­matics tools, predictive models, and data analysis pipelines to identify biomarkers and thera­peutic targets for perso­na­lized immuno­the­rapies against cancer. In close colla­bo­ration with multiple teams at TRON, as well as with partners from academia, clinics, and industry, we apply and validate our compu­ta­tional approaches and translate them into clinical practice.

The successful candidate will develop and maintain bioin­for­matics software and fully repro­du­cible, end-to-end workflows to analyze diverse biolo­gical datasets, including genomics and transcrip­tomics sequencing data from large cohorts of tumor samples.

Your tasks and respon­si­bi­lities:

• Design, implement, and maintain compu­ta­tional analysis tools and pipelines for high-throughput sequencing data, including WGS, WES, RNA-seq, scRNA-seq, spatial transcrip­tomics and long-read sequencing.
• Improve in-house bioin­for­matics pipelines to enhance accuracy, repro­du­ci­bility, and develo­pment lifecycle automation.
• Benchmark and syste­ma­ti­cally test in-house and public methods with experi­mental confir­mation data
• Build database and predictive AI systems for the discovery of novel therapy targets and biomarkers
• Provide guidance and support to PhD students and scien­tists on best practices in repro­du­cible data science and high perfor­mance compute workflows
• Colla­borate closely with multi­di­sci­plinary teams of developers, techni­cians, scien­tists, and PhD students across multiple projects

What you bring:

• MSc in Bioin­for­matics, Computer Science, or a related field
• At least two years of profes­sional experience in bioin­for­matics software develo­pment
• Advanced programming skills in Python and Nextflow; experience with R and Snakemake or other workflow languages is a plus
• Profi­ciency in struc­tured software develo­pment practices, including version control, testing, contai­ne­rization, and CI/CD systems
• Hands-on experience with Linux-based compute clusters, job schedulers, and cloud computing
• Familiarity with next-generation sequencing (NGS) data and related bioin­for­matics tools is advan­ta­geous
• Knowledge of databases and machine learning libraries is a plus

Enthu­siasm and curiosity for the diverse activities of our research institute complete your profile.

We offer:

• A dynamic, innovative, and creative research environment
• An open, collegial, and supportive working atmosphere in a respectful organiza­tional culture
• A highly diverse and inclusive workforce
• Access to our GPU-accele­rated HPC cluster and labora­tories with cutting-edge sequencing techno­logies
• Perfor­­­mance-based remune­ration and other benefits
• Oppor­tu­nities for perso­na­lized profes­sional develo­pment
• Conve­nient access via public transport and car as well as bicycle parking spaces
• The possi­bility of hybrid working arran­ge­ments

TRON is an inter­na­tio­nally recog­nised institute for appli­­­­­cation-oriented research. We combine the strengths of academic research with the requi­re­ments of quality-controlled indus­trial develo­p­ments. At TRON, we share a common mission to develop innovative solutions for the immuno­the­ra­peutic treatment of cancer, infec­tious diseases and other serious diseases with high medicinal need for develo­pment.

TRON was founded in Mainz in 2010 and works in close coope­ration with univer­sities and hospitals as well as with regional, national and inter­na­tional research insti­tu­tions and pharmaceu­tical companies.

As part of our team, you will have the oppor­tunity to work at the cutting edge of trans­la­tional science.

If all this appeals to you, we look forward to getting to know you.

Please send us your complete and infor­mative appli­cation documents (cover letter, CV, references) in a single document of max. 5 MB by e‑mail to Human Resources at jobs (at) tron-mainz.de,
Job-ID: 43104–25–01-WAMSC.

For more infor­mation, visit our homepage at www.tron-mainz.de and our GitHub page: https://github.com/TRON-Bioinformatics

In der Arbeits­gruppe von Prof. Dr. Caroline Friedel an der Ludwig-Maximi­­­lians-Univer­­­­­sität München (LMU) ist eine Stelle als

Wissenschaftliche*r Mitarbeiter*in (m/w/d)
(100 %, TV‑L E13)

im Rahmen einer Promotion zu besetzen.

Bewer­bungen sind auch willkommen, wenn Ihr Master­studium noch nicht abgeschlossen ist. Der Beginn der Promotion ist frühestens zum Oktober 2025 und spätestens zum April 2026 möglich.

Über das Projekt

Sie arbeiten im Rahmen der DFG-Forscher­­­gruppe „DEEP-DV: Gene expression and host response programming in DNA virus infection“ (https://deep-dv.org). Ziel der Arbeit ist die Entwicklung und Anwendung bioin­for­ma­ti­scher Methoden zur Analyse von Single-Cell RNA-Seq-Daten bei Infek­tionen mit verschie­denen DNA-Viren.

Ihr Profil

Sie bringen mit:

• einen abgeschlos­senen oder bald abgeschlos­senen Master in Bioin­for­matik oder einem verwandten Fach,
• fundierte Kennt­nisse in mindestens einer Program­mier­sprache (z. B. Java, R, Python),
• Interesse an der Analyse biolo­gi­scher Daten und der Entwicklung bioin­for­ma­ti­scher Werkzeuge.

Von Vorteil sind:

• Erfahrung mit Sequen­zier­daten (insbe­sondere Single-Cell RNA-Seq und/oder Spatial Transcrip­tomics

Über das Team

Die Arbeits­gruppe ist am Institut für Infor­matik der LMU angesiedelt (https://www.bio.ifi.lmu.de/~friedel). Wir befinden uns am Standort Amali­enstr. 17 in zentraler Lage in München und unmit­tel­barer Nähe zum LMU Haupt­ge­bäude. Wir sind spezia­li­siert auf die Entwicklung von Methoden für die Analyse von großen biolo­gi­schen Daten­sätzen, besonders Sequen­zier­daten, für die verschie­densten biolo­gi­schen und biome­di­zi­ni­schen Frage­stel­lungen.

Bewerbung

Bitte senden Sie Ihre Bewerbung mit den üblichen Unter­lagen (Lebenslauf, Zeugnisse oder aktuelles Transcript of Records, falls der Master noch nicht abgeschlossen ist, Bachelor- oder wenn schon vorhanden Master-Thesis) oder Fragen zur Stelle per E‑Mail an:
Prof. Dr. Caroline Friedel
Lehr- und Forschungs­einheit für Bioin­for­matik
Institut für Infor­matik
LMU München
Email: friedel-application25@bio.ifi.lmu.de

The Research Group of Compu­ta­tional Molecular Design (Prof. Matthias Rarey) has two open positions for Ph.D. students interested in developing compu­ta­tional methods for early-phase drug discovery. If you have a degree in bioin­for­matics, compu­ta­tional chemistry, or a related field at the inter­section of computer science and life sciences, and are interested in starting your career in the exciting field of drug discovery, please get in touch. We are looking for two talented Ph.D. students with a strong background in computer science (algorithmics, machine learning, and advanced programming) and the natural sciences (preferably struc­tural biology, organic chemistry, and physical chemistry). Our research group has a high inter­na­tional reputation and contacts with dozens of pharmaceu­tical companies around the world. We also have a highly profes­sio­na­lized software develo­pment infra­structure, including group-dedicated system adminis­tration and scien­tific software engineering. Details about the positions can be found at

https://www.zbh.uni-hamburg.de/en/service/stellen.html.

Feel free to contact us at rarey-office.zbh@uni-hamburg.de with any questions.