During mammalian sex determination, the bipotential embryonic gonad adopts either testicular or ovarian cell fates. This process highly relies on precise expression of several pro-male versus pro-female factors, most of which are transcription factors (TFs) and signalling pathway components. Yet, we still do not understand the interplay and hierarchy among these factors, their direct target genes, the regulatory elements they bind to, nor do we have an in vitro system to address these questions. We recently explored the complex gene expression regulation of Sox9, a key pro-male factor, and identified several active testis-specific enhancers. Remarkably, deletion of one of these led to XY male-to-female sex reversal in mice. The presence of several functional enhancers highlights the complex gene expression regulation present during sex determination, which we aim to address here in a systematic manner. Furthermore, we recently developed a system to generate mouse and human gonadal progenitors from embryonic stem cells. Building on our exciting results, we seek to decipher the gene regulatory networks governing mammalian sex determination using in vivo and in vitro approaches. This proposal will pursue three complementary aims: (i) Identify target genes of the key factors controlling gonad formation; (ii) Map the regulatory elements bound by these factors; (iii) Develop an in vitro organoid system to model testis development. Using cutting edge techniques as CUT&RUN ChIP-Seq, ATAC-Seq, Promoter Capture Hi-C, CRISPR genome editing, organoid culture and 3D scaffolding development, we will address the complex gene expression regulation governing sex determination. Insights gained from this basic research will shed light on cell fate decisions in general, allow better diagnosis of many patients with Disorders of Sex Development, and offer an in vitro system to study gonad development and function with implications for understanding and treating infertility.

Exploring the effect of School Ethical Culture (SEC) on students' science achievements is the goal of this study. The integrative model that I propose demonstrates the impact of both external and internal school factors on the TIMSS 2011 assessments. The originality of this proposal is rooted in three points: (A) The fact that the focus on SEC as a predictor of student achievement in science is currently unnoticed in international assessment studies; (B) No previous study has investigated the differences in SEC among participating countries; and (C) This study focuses on ethical perceptions from the viewpoints of principals, students, and teachers. Addressing the study's objective, I will conduct a multi-international disciplinary study that will draw on data from approximately 45 countries, including much of Europe and others. The study will examine the dimensions of SEC separately for teachers, students, and principals by calculating the factor loadings of the latent SEC for each questionnaire and applying hierarchical linear modelling to estimate the effect of student-, school- and country-level on science achievement. The hope is that the findings will prompt a rethinking of analytical models of schooling and facilitate the design of ethical policies that could narrow achievement gaps. This approach could establish a new research field in education. The proposed study will draw on Prof. Benavot’s supervision (outgoing host, SUNY at Albany), and his close contacts with many European researchers, as well as on Dr. Klein's (supervisor, return host, BIU) expertise in effective learning and national assessments. I see great potential for using this study to establish long-term collaborations with European and American scientists through my experience and contacts with other European researchers. Moreover, this fellowship will deepen my research, facilitating my advancement to the next stage of my academic career.

The advances in technology over the last decade and the massive amount of data passing through the internet has intrigued and challenged computer scientists, as the old models of computation used before this era are now less relevant or too slow. New computational models have been suggested to tackle these technological advances. In the most basic sense, these modern models allow one to scan the input only once, possible with small auxiliary memory. Nevertheless, modern techniques have also been introduced such as sparse recovery which has proven to be a very useful tool for dealing with modern challenges, and the very popular notion of conditional lower bounds which has provided evidence of hardness for various algorithmic tasks based on very popular conjectures. Pattern matching plays a crucial role in many computing applications that can be seen in day to day life. However, its research community has only recently started gaining insight on what can be done in modern models, and is lagging behind in this respect. In particular, there are no algorithms for pattern matching problems that have utilized ideas from sparse recovery, and only recently has there been progress in proving conditional lower bounds for string problems. Furthermore, conditional lower bounds suffer from the lack of hardness conjectures which address time/space tradeoffs. This proposal will close this gap for many important pattern matching problems within the new models of computation, and will be the first to utilize modern algorithmic techniques, such as sparse recovery, and adapting them into the pattern matching world. Furthermore, this proposal will focus on developing a theory for proving conditional time/space lower bounds, based on new hardness conjectures. This will greatly influence not only the pattern matching sub-field, but the entire algorithmic field at large.