Drug discovery is a complex process relying on model systems to estimate the toxicity of drugs in humans. While drug discovery benefitted greatly from the integration of computational methods in research projects the translational step from in vitro and in vivo model systems to patients is relatively unsuccessful.
The eTransafe consortium is a European project for new drug safety assessment and integrative data analysis research. eTransafe aims to develop an advanced data integration infrastructure together with innovative computational methods to improve the security in drug development process and is funded by the Innovative Medicines Initiative 2 Joint Undertaking (IMI 2) together with the pharmaceutical industry. 

Currently we are looking for a PhD student that will work within this consortium. LACDR is involved in several work packages, one of which is multi-scale predictive modeling approaches. The approaches aim to predict preclinical toxicity and provide translational tools to predict human toxicity and drug side effects. 
For this project, tasks include: 

• Use machine learning tools such as ‘deep learning’ to predict to which proteins molecules will bind;
• Combine multiple models using ensemble-modeling approaches to improve predictions and estimate model errors;
• Use molecular modeling techniques to understand chemical to protein interactions at the molecular level;
• Link predicted molecular interactions to adverse outcome pathways;
• Apply models predictions and adverse outcome pathways modeling to understand toxicity and side effects;
• Collaborate within LACDR with scientists working in other projects that can benefit from big data analysis in their project;
• Collaborate with experts from the Leiden Institute of Advanced Computers Science (LIACS);
• Working together with multiple universities and pharma companies in Europe to develop these predictive models that can be used in drug discovery. 

Importantly, this is a multi-disciplinary project wherein scientists with diverse background (machine learning, cheminformatics, data-mining, experimental) will be working together. 

• The candidate has (or will receive in near future) a master’s degree in (bio)pharmaceutical sciences, computer sciences, or equivalent;
• The candidate should have excellent multidisciplinary team working and communication skills;
• Affinity with computational sciences, machine learning, experience with UNIX/Linux operating systems, and experience with scripting are advantageous benefits. 

Fixed-term contract: 4 years.

We offer a position for initially one year. After a positive evaluation of the progress of the thesis, personal capabilities and compatibility the appointment will be extended by a further three years. Salary ranges from €2,222 to €2,840 gross per month (pay scale P in accordance with the Collective Labour Agreement for Dutch Universities).

Leiden University offers an attractive benefits package with additional holiday (8%) and end-of-year bonuses (8.3 %), training and career development and sabbatical leave. Our individual choices model gives you some freedom to assemble your own set of terms and conditions. Candidates from outside the Netherlands may be eligible for a substantial tax break. More at www.workingat.leiden.edu/. 

The appointment should lead to a dissertation (PhD thesis). A training & supervision plan will be drafted, including attendance of courses and (international) meetings. The PhD-student is also expected to assist in teaching undergraduates.
All our PhD students are embedded in the Leiden University Graduate School of Science (www.graduateschools.leidenuniv.nl/). Our Graduate School offers several PhD training courses at three levels: professional courses, skills training and personal effectiveness. In addition, advanced courses to deepen scientific knowledge are offered by the research school.

Diversity
Leiden University is strongly committed to diversity within its community and especially welcomes applications from members of underrepresented groups.

Universiteit Leiden

Leiden is a typical university city, hosting the oldest university in the Netherlands (1575). The University permeates the local surroundings; University premises are scattered throughout the city, and the students who live and study in Leiden give the city its relaxed yet vibrant atmosphere.

Leiden University is one of Europe's foremost research universities. This prominent position gives our graduates a leading edge in applying for academic posts and for functions outside academia.

https://www.universiteitleiden.nl/

Faculty of Science

The Faculty of Science is a world-class faculty where staff and students work together in a dynamic international environment. It is a faculty where personal and academic development are top priorities. Our people are committed to expand fundamental knowledge by curiosity and to look beyond the borders of their own discipline; their aim is to benefit science, and to make a contribution to addressing the major societal challenges of the future. The research carried out at the Faculty of Science is very diverse, ranging from mathematics, information science, astronomy, physics, chemistry and bio-pharmaceutical sciences to biology and environmental sciences. The research activities are organised in eight institutes. These institutes offer eight bachelor’s and twelve master’s programmes. The faculty has grown strongly in recent years and now has more than 1,300 staff and almost 4,000 students. We are located at the heart of Leiden’s Bio Science Park, one of Europe’s biggest science parks, where university and business life come together. For more information, see www.universiteitleiden.nl/en/science.

The Leiden Academic Centre for Drug Research (LACDR) is a leading institute dedicated to world-class research and education in drug discovery and development. LACDR comprises a diverse and international team of 150 researchers and is ideally located at the Leiden Bio Science Park, the largest life science cluster in the Netherlands. The PhD candidate will be working in the ‘Computational Chemical Biology’ group together with a team of PhD candidates that work on related projects. In our group we focus mostly on two key research areas: structure based methods (molecular modeling) and leveraging diverse and large-scale public data (‘big data’; cheminformatics, bioinformatics, and data mining).  These techniques are both investigated on their own (can we discover better ways to do computational research) and applied (can we use these methods to answer scientific questions in the context of a research project). For more information and a better understanding please see  https://www.universiteitleiden.nl/en/research/research-projects/science/lacdr-computational-chemical-biology.

https://www.universiteitleiden.nl/en/science