Doctoral Candidate Position 4 - Bayer A.G. Germany
AI-driven data analysis, target identification and treatment development in PD
Description of project
Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by the loss of dopaminergic neurons in the substantia nigra, leading to motor symptoms such as tremors, rigidity, and bradykinesia. Recent research has highlighted the complex interplay between the nervous and immune systems in PD pathogenesis, emphasizing the need for integrated approaches to study neuro-immune interactions. This project aims to research best practices for, and develop novel collaborative no-code analytical platform specifically designed to explore and analyze neuro-immune interfaces in the context of PD and other neurodegenerative diseases.
The research will first focus on full integration and making easily accessible evidence from both user-provided data and publicly available biomedical databases and literature sources, adhering to FAIR (Findable, Accessible, Interoperable, and Reusable) principles. This will be followed by the representation of data in a knowledge graph, enabling sophisticated reasoning and hypothesis generation. Finally, the project will establish explainable AI-powered analytics, reasoning, hypothesis generation, and ranking pipelines about targets, pathways, and potential treatments.
The platform will incorporate various data types, including genetic, biochemical, and clinical information, to provide a comprehensive view of the neuro-immune landscape in PD. By leveraging advanced machine learning techniques and natural language processing, the system will be able to analyze and integrate results from multiple experimental studies, literature sources, and other relevant data repositories. This multidisciplinary approach combines techniques from computer science, bioinformatics, and neuroscience to create a powerful tool for PD research.
Expected outcomes of this project include determining the precise best practices for multi-layered analysis of targets involved in neurodegenerative diseases and developing a system that can help scientists collaborate, review, analyze, and integrate results from diverse sources.
Ultimately, this work could lead to the identification of novel therapeutic targets and potential treatments for PD by facilitating a deeper understanding of the complex neuro-immune interactions underlying the disease. The collaborative nature of the platform will foster interdisciplinary research and accelerate the pace of discovery in the field of neurodegenerative diseases.
Required selection criteria
- Excellent track record in relation to the opportunity
- Completed Master's degree (or equivalent) in Computer Science, Mathematics, Physics, Biology, Medicine or related
- Excellent programming in at least one programming language, preferably Python
- Very good communication and collaboration skills and fluency in English
Preferred selection criteria
- Experience in working with data integration and big data
- Experience in machine learning frameworks, such as PyTorch, Tensorflow, Jax or similar
- Experience in time management and teamwork
- Above-average commitment, ability to work independently and integrate into an interdisciplinary team
- Scientific curiosity and passion
Specific Requirements
- Must not already hold a doctoral degree
- Must comply with the MSC Action mobility rule: not have resided or carried out their main activity (work, studies, etc.) in Germany for more than 12 months in the 3 years immediately before the recruitment date.
- You must meet the requirements for admission to the Graduate School of Freie University Berlin
Benefits
- Access to state-of-the-art training within the BICEPS doctoral network, at an academic, and industry level
- Opportunities to collaborate with discipline specific world leading researchers
- A mobility allowance to support relocation
- A family allowance for the relocation of family (terms and conditions apply)
Eligibility criteria
The company has a continuing commitment to equal employment opportunity and affirmative action. Our policy of equal employment opportunity is founded on sound business judgment and a basic respect for the individual. This commitment reaches into all areas of the company. For example, it is reflected in our advertising, recruiting, interviewing, testing and training; in our employment, promotion and compensation policies, separation practices; and, in our employee benefits programs.
Hiring and advancement are based on job-related requirements and on an individual's qualifications to perform a job. All aspects of employment are carried out free of discrimination or harassment based on race, color, religion, sex (including pregnancy), national origin, age, disability, genetic information, veteran status, sexual orientation, gender identity/gender expression or any other characteristic protected by federal, state, or local law. Also, it is a violation of this policy, to subject any individual to
retaliation, for exercising their right to report an incident involving discrimination or harassment based upon a protected category.
Selection process
The application and supporting documentation to be used as the basis for the assessment must be in English. Applications should include:
- Complete CV (name, address, degree(s) with transcript(s) of grades, research experience, educational and employment history, publications etc.)
- Letter of application (max. 1 page) including a short explanation of the applicant’s motivation to undertake a PhD
- Transcripts and diplomas for bachelor's and master's degrees
- Names, contact details (including email addresses) of at least two referees
If all, or parts, of your education have been completed abroad, we also ask you to attach documentation of the scope and quality of your entire education, both bachelor's and master's education, in addition to other higher education. Upon request, you must be able to obtain certified copies of your documentation.
Please use the harmonized Application Form before the deadline of 15-February 2025. Candidates are encouraged to apply early. Applications will be accepted until this deadline and considered on a rolling basis until the position is filled.
Applications submitted by post or email will not be considered. Upon request, you must be able to obtain certified copies of your documentation.
In the evaluation of which candidate is best qualified, emphasis will be placed on education, experience, and personal and interpersonal qualities.
Additional comments
Bayer is a Life Science company with a more than 150-year history and core competencies in the areas of health care and agriculture. With our innovative products, we are contributing to finding solutions to some of the major challenges of our time. A growing and aging world population requires an adequate supply of food and improved medical care. With our innovative products, we are contributing to finding solutions to some of the major challenges of our time. With life expectancy continuing to rise, we improve quality of life for a growing population by focusing our research and development activities on preventing, alleviating and treating diseases. We are also making an important contribution to providing a reliable supply of high-quality food, feed and plant-based raw materials.
The position is limited to a period of 4 years. The first year constitutes a probationary period, with an evaluation of the candidate's performance after 6 months. The objective of this evaluation is to establish whether the candidate will be able to finish a PhD thesis in the remaining period. If the performance evaluation is positive, the candidate's contract will be extended to the full period, when it is expected that the candidate will be able to finish their thesis. Successful candidates may be offered permanent role after finishing their degree.