激酶药物发现深度学习、AI与化学信息学方向博士研究员（科研助理，薪级 P）

The Faculty of Science and Leiden Academic Centre for Drug Research (LACDR) are looking for candidates for a PhD Position (Doctoral Candidate 10) in the Marie Skłodowska-Curie Doctoral Network ANA-KIN

ANA-KIN is a Marie Skłodowska-Curie Actions (MSCA) Doctoral Network funded by the European Union’s Horizon Europe programme. Over the past two decades, small-molecule kinase inhibitors have transformed cancer therapy, yet nearly all of them target the highly conserved ATP-binding site, which limits selectivity and allows resistance to emerge. ANA-KIN aims to train a new generation of interdisciplinary researchers capable of redefining kinase drug discovery beyond the ATP paradigm, by developing the experimental and computational tools, modular assays and workflows needed to systematically target non-conserved regulatory interfaces, such as kinase dimerization and substrate-binding sites. Proof-of-concept will be demonstrated on three representative kinases: EGFR, BRAF and the understudied “dark” kinase LTK.

ANA-KIN brings together 11 beneficiaries and 9 associated partners across Europe and the USA, including Aristotle University of Thessaloniki (coordinator), University of Crete, Goethe University Frankfurt, Saarland University, EPFL, CNRS, Pompeu Fabra University, VIB, KU Leuven, INSERM and Leiden University, together with industrial partners such as AstraZeneca, Novartis, Servier and Skylight Therapeutics. The network combines chemical biology, structural biophysics (single-molecule FRET, cryo-EM, nanodiscs), AI-driven drug design and cell biology in an integrated learn–design–test loop. Twelve Doctoral Candidates (DCs) will each pursue an individual research project, benefit from co-supervision across institutions and sectors, carry out two research secondments at partner organizations, and follow a structured network-wide training program covering scientific, transferable, open-science and entrepreneurial skills.

In this PhD project (DC10, Work Package 3 – Discovery), you will develop deep-learning architectures that integrate text-mined, cheminformatic, and biophysical descriptors to predict interface binding, allosteric signatures and resistance liabilities of kinase ligands. The models will learn jointly across peptide and small-molecule modalities and will be used to generate hybrid peptidomimetic design hypotheses. You will translate these models into consortium-wide prioritisation dashboards that support hit triage and analogue selection in the discovery campaigns of ANA-KIN, and work in close reciprocal feedback with DC9 (Saarland University) on structure-based and machine-learning pipelines. Model predictions will be validated prospectively with the experimental partners in the network.

The expected results are a resistance-aware AI workflow for non-ATP interface ligands, accompanied by public models, datasets and interpretable feature maps, and prospective design case studies demonstrating improved optimisation trajectories. To reinforce structural grounding and experimental validation, you will carry out two secondments: at VIB (Belgium, Prof. Ruslan Efremov; 4 months) to extract structural classes and conformational features from cryo-EM data and use them to refine model constraints, and at Skylight Therapeutics (Belgium, Dr. Joshua Salafsky; 3 months) to test model predictions using second-harmonic generation (SHG)-based conformational profiling. The project will be supervised by Prof. Gerard J.P. van Westen (Leiden University), with Prof. Ruslan Efremov and Dr. Joshua Salafsky as co-supervisors.

What you will do • Conduct original and novel research in deep learning, AI, and cheminformatics for kinase drug discovery; • Develop, benchmark and openly share models, datasets and decision-support dashboards following FAIR and open-science principles; • Collaborate closely with experimental and computational DCs in the network, and carry out two research secondments abroad (VIB and Skylight Therapeutics, Belgium); • Publish and present scientific articles at international journals and conferences; • Participate in the ANA-KIN network-wide training events, schools and outreach activities; • Contribute to educational activities; • Write a dissertation.

What you bring • A MSc degree in Computer Science, AI, (Computational) Chemistry, Bioinformatics, Biopharmaceutical Sciences, or a relevant related field; • Good knowledge of and experience with machine learning and deep-learning techniques (e.g. PyTorch); • Good knowledge of and experience with cheminformatics and/or computational chemistry (e.g. RDKit, molecular descriptors, docking); • Interest in structural biology, protein kinases and drug discovery; affinity with peptide or biophysical data is an advantage; • Highly motivated to both perform foundational research and apply the developed methods to real-world problems; creative, ‘making things work’ mentality, independent, and communicative team player; • Willingness to travel and to carry out research secondments at partner institutions abroad; • Excellent programming skills (preferably Python); • Good academic writing skills and interest in participating in educational activities; • Excellent proficiency in English (oral and written).

MSCA eligibility criteria • At the date of recruitment, candidates must not have been awarded a doctoral degree; • Mobility rule: candidates must not have resided or carried out their main activity (work, studies, etc.) in the Netherlands for more than 12 months in the 36 months immediately before the date of recruitment. Compulsory national service, short stays such as holidays, and time spent as part of a procedure for obtaining refugee status are not taken into account.

Where you will work

Leiden Academic Centre for Drug Research Our institute is a center of excellence for multidisciplinary research on drug discovery and development. Leiden University consistently ranks within the top-20 world-wide within the subject-based QS Ranking in Pharmacology and Pharmacy. At LACDR, we develop innovative scientific concepts in fundamental and translational research underlying the discovery and optimization of drugs, and personalized medicines. We aim to optimize the route to novel drugs that are both efficacious and safe, and therefore our research focuses on drug discovery and safety, bio-therapeutics, and systems biomedicine and pharmacology. State-of-the-art expertise and infrastructures ensure that we are strategically positioned in (inter)national collaborations, thus further strengthening the development of novel concepts and their application in a clinical and industry environment.

Computational Drug Discovery Research in this group, headed by Gerard van Westen, focusses on computational methods integrated in different parts of the drug discovery process. More specifically, topics include innovative treatments for cancer, kinase and GPCR drug discovery, proteochemometrics, selectivity and polypharmacology modeling, allosteric modulation, drug resistance modeling, de novo molecular design, and novel methods in the domain of machine learning. For more information see: http://www.cddl.nl

Research at our faculty 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 diverse, ranging from artificial intelligence, computer science, mathematics, astronomy, physics, chemistry and bio-pharmaceutical sciences to biology and environmental sciences. The faculty has grown strongly in recent years and now has more than 2,700 staff and almost 6,000 students. We are located in the heart of the Bio Science Park, one of Europe’s largest science parks, where academia and industry meet. For more information, see http://www.science.leidenuniv.nl .

What we offer We offer a full-time appointment for 48 months as a Doctoral Candidate within the MSCA Doctoral Network ANA-KIN, starting late 2026. The appointment is initially for one year; after a positive evaluation of the progress of the research, personal capabilities and compatibility, the appointment will be extended for the remaining period. Salary ranges from € 3.204,- tot € 4.051,- gross per month (pay scale P in accordance with the Collective Labor 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. 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.

All our PhD students are embedded in the Leiden University Graduate School of Science. 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. As an ANA-KIN Doctoral Candidate you will also follow the network’s training program, including summer schools, workshops and an industrial immersion workshop, and your progress will be monitored by a Thesis Advisory Committee including an independent mentor.

What we value Promoting an inclusive community is central to Leiden University’s values and vision. We strive to be an open community in which all students and staff members feel valued and respected, and are able to fully develop themselves. We consider an inclusive academic environment, where students and staff can share their experiences and viewpoints, to be essential for the development of talent.

Want to apply or find out more? Inquiries about the research area can be made to Prof. Gerard van Westen, gerard@lacdr.leidenuniv.nl. If you have any questions about the procedure, please contact Brigitte Kraakman, b.p.m.kraakman@lacdr.leidenuniv.nl. To apply for this vacancy, please submit your application online via the blue button below. Please ensure that you upload the following additional documents quoting the vacancy number and “ANA-KIN DC10”: • application letter (including a statement confirming that they meet the MSCA eligibility criteria) • curriculum vitae • a list of grades • two references (who have agreed to be contacted)

Only applications received no later than November 12th can be considered. The selection procedure will take place in November. Selected candidates may be invited for an interview in the last week of November / 1st week of December, during which you are kindly requested to be available. • Acquisition in response to this vacancy is not appreciated. If you nevertheless choose to send us CVs, no rights can be derived from this. #LI-Hybrid